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@article{plate_holographic_1995,
title = {Holographic reduced representations},
volume = {6},
issn = {10459227},
url = {http://ieeexplore.ieee.org/document/377968/},
doi = {10.1109/72.377968},
abstract = {Associative memories are conventionally used to represent data with very simple structure: sets of pairs of vectors. This paper describes a method for representing more complex compositional structure in distributed representations. The method uses circular convolution to associate items, which are represented by vectors. Arbitrary variable bindings, short sequences of various lengths, simple frame-like structures, and reduced representations can be represented in a fixed width vector. These representations are items in their own right and can be used in constructing compositional structures. The noisy reconstructions extracted from convolution memories can be cleaned up by using a separate associative memory that has good reconstructive properties.},
language = {en},
number = {3},
urldate = {2020-11-03},
journal = {IEEE Transactions on Neural Networks},
author = {Plate, T.A.},
month = may,
year = {1995},
keywords = {Associative memory, Artificial intelligence, associative processing, Cancer, circular convolution, compositional structures, Concrete, content-addressable storage, convolution, Convolution, Councils, Degradation, holographic reduced representations, holographic storage, Holography, neural nets, Tree data structures, vectors},
pages = {623--641},
annote = {Conference Name: IEEE Transactions on Neural Networks},
file = {Plate_1995_Holographic_reduced_representations.pdf:files/5836/Plate_1995_Holographic_reduced_representations.pdf:application/pdf},
}
@article{bogacz_extending_2007,
title = {Extending a biologically inspired model of choice: multi-alternatives, nonlinearity and value-based multidimensional choice},
volume = {362},
issn = {0962-8436, 1471-2970},
shorttitle = {Extending a biologically inspired model of choice},
url = {https://royalsocietypublishing.org/doi/10.1098/rstb.2007.2059},
doi = {10.1098/rstb.2007.2059},
abstract = {The leaky competing accumulator (LCA) is a biologically inspired model of choice. It describes the processes of leaky accumulation and competition observed in neuronal populations during choice tasks and it accounts for reaction time distributions observed in psychophysical experiments. This paper discusses recent analyses and extensions of the LCA model. First, it reviews the dynamics and examines the conditions that make the model achieve optimal performance. Second, it shows that nonlinearities of the type present in biological neurons improve performance when the number of choice alternatives increases. Third, the model is extended to value-based choice, where it is shown that nonlinearities in the value function explain risk aversion in risky choice and preference reversals in choice between alternatives characterized across multiple dimensions.},
language = {en},
number = {1485},
urldate = {2020-11-03},
journal = {Philosophical Transactions of the Royal Society B: Biological Sciences},
author = {Bogacz, Rafal and Usher, Marius and Zhang, Jiaxiang and McClelland, James L},
month = sep,
year = {2007},
note = {Number: 1485},
pages = {1655--1670},
file = {Bogacz_et_al_2007_Extending_a_biologically_inspired_model_of_choice.pdf:files/5779/Bogacz_et_al_2007_Extending_a_biologically_inspired_model_of_choice.pdf:application/pdf},
}
@article{krajbich_multialternative_2011,
title = {Multialternative drift-diffusion model predicts the relationship between visual fixations and choice in value-based decisions},
volume = {108},
issn = {0027-8424, 1091-6490},
url = {http://www.pnas.org/cgi/doi/10.1073/pnas.1101328108},
doi = {10.1073/pnas.1101328108},
language = {en},
number = {33},
urldate = {2020-11-03},
journal = {Proceedings of the National Academy of Sciences},
author = {Krajbich, I. and Rangel, A.},
month = aug,
year = {2011},
note = {Number: 33},
pages = {13852--13857},
file = {Krajbich_Rangel_2011_Multialternative_drift-diffusion_model_predicts_the_relationship_between_visual.pdf:files/5774/Krajbich_Rangel_2011_Multialternative_drift-diffusion_model_predicts_the_relationship_between_visual.pdf:application/pdf},
}
@article{chi_icap_2014,
title = {The {ICAP} {Framework}: {Linking} {Cognitive} {Engagement} to {Active} {Learning} {Outcomes}},
volume = {49},
issn = {0046-1520, 1532-6985},
shorttitle = {The {ICAP} {Framework}},
url = {http://www.tandfonline.com/doi/abs/10.1080/00461520.2014.965823},
doi = {10.1080/00461520.2014.965823},
language = {en},
number = {4},
urldate = {2020-11-03},
journal = {Educational Psychologist},
author = {Chi, Michelene T. H. and Wylie, Ruth},
month = oct,
year = {2014},
note = {Number: 4},
pages = {219--243},
file = {Chi_Wylie_2014_The_ICAP_Framework.pdf:files/5780/Chi_Wylie_2014_The_ICAP_Framework.pdf:application/pdf},
}
@article{qiu_neural_2018,
title = {The neural system of metacognition accompanying decision-making in the prefrontal cortex},
volume = {16},
issn = {1545-7885},
url = {https://dx.plos.org/10.1371/journal.pbio.2004037},
doi = {10.1371/journal.pbio.2004037},
abstract = {Decision-making is usually accompanied by metacognition, through which a decision maker monitors uncertainty regarding a decision and may then consequently revise the decision. These metacognitive processes can occur prior to or in the absence of feedback. However, the neural mechanisms of metacognition remain controversial. One theory proposes an independent neural system for metacognition in the prefrontal cortex (PFC); the other, that metacognitive processes coincide and overlap with the systems used for the decision-making process per se. In this study, we devised a novel “decision–redecision” paradigm to investigate the neural metacognitive processes involved in redecision as compared to the initial decision-making process. The participants underwent a perceptual decision-making task and a rule-based decision-making task during functional magnetic resonance imaging (fMRI). We found that the anterior PFC, including the dorsal anterior cingulate cortex (dACC) and lateral frontopolar cortex (lFPC), were more extensively activated after the initial decision. The dACC activity in redecision positively scaled with decision uncertainty and correlated with individual metacognitive uncertainty monitoring abilities—commonly occurring in both tasks—indicating that the dACC was specifically involved in decision uncertainty monitoring. In contrast, the lFPC activity seen in redecision processing was scaled with decision uncertainty reduction and correlated with individual accuracy changes—positively in the rule-based decision-making task and negatively in the perceptual decision-making task. Our results show that the lFPC was specifically involved in metacognitive control of decision adjustment and was subject to different control demands of the tasks. Therefore, our findings support that a separate neural system in the PFC is essentially involved in metacognition and further, that functions of the PFC in metacognition are dissociable.},
language = {en},
number = {4},
urldate = {2020-11-03},
journal = {PLOS Biology},
author = {Qiu, Lirong and Su, Jie and Ni, Yinmei and Bai, Yang and Zhang, Xuesong and Li, Xiaoli and Wan, Xiaohong},
editor = {Rushworth, Matthew},
month = apr,
year = {2018},
note = {Publisher: Public Library of Science},
keywords = {Prefrontal cortex, Control theory, Behavior, Cingulate cortex, Decision making, Decision theory, Functional magnetic resonance imaging, Metacognition},
pages = {e2004037},
file = {Qiu_et_al_2018_The_neural_system_of_metacognition_accompanying_decision-making_in_the.pdf:files/5773/Qiu_et_al_2018_The_neural_system_of_metacognition_accompanying_decision-making_in_the.pdf:application/pdf},
}
@incollection{alexandre_behavioral_2017,
address = {Chichester, UK},
title = {A {Behavioral} {Framework} for {Information} {Representation} in the {Brain}},
isbn = {978-1-119-15919-3 978-1-119-15901-8 978-1-119-15906-3},
url = {http://doi.wiley.com/10.1002/9781119159193.ch29},
abstract = {Along evolution, increasingly complex cognitive functions have been attributed to an increasingly complex brain architecture. Nevertheless, the brain remains anchored on an organization dedicated to survival. We believe that keeping this principle in mind is an excellent way to better decipher cerebral mechanisms and corresponding cognitive functions. Accordingly, we describe here the main characteristics and constraints of an intelligent agent learning to survive in an intelligent environment, in terms of information flows and learning principles. On this basis, we propose a framework of description for the architecture of the brain of mammals, organized around four fundamental questions to be answered. These questions define the identity of the goal (what ?) and the motivation to choose it (why ?), its location (where ?) and the way to get it (how ?). Then we explain how the main requirements of respondent and operant conditioning can be addressed within this architecture and how it is also compatible with the elaboration of more complex cognitive mechanisms. This can be seen as the validation of this framework to explore how cognitive functions might emerge from cerebral circuits and how they have been made more complex along evolution. It also proposes a systemic view of the brain, useful to develop the cognitive architecture of an intelligent agent exploring autonomously its environment and to propose to machine learning innovative algorithms.},
language = {en},
urldate = {2020-11-03},
booktitle = {Computational {Models} of {Brain} and {Behavior}},
publisher = {John Wiley \& Sons, Ltd},
author = {Alexandre, Frédéric},
editor = {Moustafa, Ahmed A.},
month = sep,
year = {2017},
doi = {10.1002/9781119159193.ch29},
pages = {401--412},
file = {Alexandre_2017_A_Behavioral_Framework_for_Information_Representation_in_the_Brain.pdf:files/5784/Alexandre_2017_A_Behavioral_Framework_for_Information_Representation_in_the_Brain.pdf:application/pdf},
}
@incollection{romero_analyse_2021,
title = {Analyse d'activités d'apprentissage médiatisées en robotique pédagogique},
url = {https://hal.inria.fr/hal-02957270},
language = {fr},
urldate = {2020-11-03},
booktitle = {Traité de méthodologie de la recherche en {Sciences} de l’Éducation et de la {Formation}},
publisher = {B. Alberto and J.Thievenaz},
author = {Romero, Margarida and Vieville, Thierry and Heiser, Laurent},
year = {2021},
note = {Publisher: Unpublished},
file = {Romero_et_al_2021_Analyse_d'activites_d'apprentissage_mediatisees_en_robotique_pedagogique.pdf:files/5771/Romero_et_al_2021_Analyse_d'activites_d'apprentissage_mediatisees_en_robotique_pedagogique.pdf:application/pdf},
}
@article{bogacz_dopamine_2020,
title = {Dopamine role in learning and action inference},
volume = {9},
issn = {2050-084X},
url = {https://elifesciences.org/articles/53262},
doi = {10.7554/eLife.53262},
abstract = {This paper describes a framework for modelling dopamine function in the mammalian brain. It proposes that both learning and action planning involve processes minimizing prediction errors encoded by dopaminergic neurons. In this framework, dopaminergic neurons projecting to different parts of the striatum encode errors in predictions made by the corresponding systems within the basal ganglia. The dopaminergic neurons encode differences between rewards and expectations in the goal-directed system, and differences between the chosen and habitual actions in the habit system. These prediction errors trigger learning about rewards and habit formation, respectively. Additionally, dopaminergic neurons in the goal-directed system play a key role in action planning: They compute the difference between a desired reward and the reward expected from the current motor plan, and they facilitate action planning until this difference diminishes. Presented models account for dopaminergic responses during movements, effects of dopamine depletion on behaviour, and make several experimental predictions.},
language = {en},
urldate = {2020-11-03},
journal = {eLife},
author = {Bogacz, Rafal},
month = jul,
year = {2020},
pages = {e53262},
file = {Bogacz_2020_Dopamine_role_in_learning_and_action_inference.pdf:files/5782/Bogacz_2020_Dopamine_role_in_learning_and_action_inference.pdf:application/pdf},
}
@inproceedings{levy_vector_2008,
title = {Vector {Symbolic} {Architectures}: {A} {New} {Building} {Material} for {Artificial} {General} {Intelligence}},
abstract = {We provide an overview of Vector Symbolic Architectures (VSA), a class of structured associative memory models that offers a number of desirable features for artificial general intelligence. By directly encoding structure using familiar, computationally efficient algorithms, VSA bypasses many of the problems that have consumed unnecessary effort and attention in previous connectionist work. Example applications from opposite ends of the AI spectrum – visual map-seeking circuits and structured analogy processing – attest to the generality and power of the VSA approach in building new solutions for AI.},
language = {en},
booktitle = {Frontiers in {Artificial} {Intelligence} and {Applications}},
author = {Levy, Simon D and Gayler, Ross},
year = {2008},
pages = {6},
file = {Levy_Gayler_2008_Vector_Symbolic_Architectures.pdf:files/5840/Levy_Gayler_2008_Vector_Symbolic_Architectures.pdf:application/pdf},
}
@article{rodriguez-arias_intelligent_2020,
title = {An {Intelligent} and {Collaborative} {Multiagent} {System} in a {3D} {Environment}},
volume = {54},
issn = {2504-3900},
url = {https://www.mdpi.com/2504-3900/54/1/36},
doi = {10.3390/proceedings2020054036},
abstract = {Multiagent systems (MASs) allow facing complex, heterogeneous, distributed problems difficult to solve by only one software agent. The world of video games provides problems and suitable environments for the use of MAS. In the field of games, Unity is one of the most used engines and allows the development of intelligent agents in virtual environments. However, although Unity allows working in multiagent environments, it does not provide functionalities to facilitate the development of MAS. The aim of this work is to create a multiagent system in Unity. For this purpose, a predator–prey problem was designed in which the agents must cooperate to arrest a thief driven by a human player. To solve this cooperative problem, it is required to create the representation of the environment and the agents in 3D; to equip the agents with vision, contact, and sound sensors to perceive the environment; to implement the agents’ behaviors; and, finally but not less important, to build a communication system between agents that allows negotiation, collaboration, and cooperation between them to create a complex, role-based chasing strategy.},
language = {en},
number = {1},
urldate = {2020-11-03},
journal = {Proceedings},
author = {Rodríguez-Arias, Alejandro and Guijarro-Berdiñas, Bertha and Sánchez-Maroño, Noelia},
month = aug,
year = {2020},
note = {Number: 1},
pages = {36},
file = {Rodriguez-Arias_et_al_2020_An_Intelligent_and_Collaborative_Multiagent_System_in_a_3D_Environment.pdf:files/5834/Rodriguez-Arias_et_al_2020_An_Intelligent_and_Collaborative_Multiagent_System_in_a_3D_Environment.pdf:application/pdf},
}
@inproceedings{repetto_semantic_2015,
address = {Torino, Italy},
title = {A {Semantic} {Layer} for {Knowledge}-{Based} {Game} {Design} in {Edutainment} {Applications}},
isbn = {978-1-63190-061-7},
url = {http://eudl.eu/doi/10.4108/icst.intetain.2015.259561},
doi = {10.4108/icst.intetain.2015.259561},
abstract = {Creating and maintaining complex and realistic virtual worlds is still a challenge in game design. Realism is not only related to visual appearance but also to the interactions and situations in the game. This issue is particularly crucial in edutainment applications where realism impacts the learning aspect of the game experience. Introducing semantics in virtual worlds helps define intelligent objects and interactions which would turn into a more realistic game. In this work, we propose to decouple the semantic definition of the game world from its actual implementation in a general-purpose game engine. A semantic layer has been developed to bridge the semantics formalized by ontologies with its realization in the engine. Thanks to this software library, semantics can be specified in a separate formal module and reused in different projects. The proposed approach has been tested to design a serious game concept set in the marine environment.},
language = {en},
urldate = {2020-11-03},
booktitle = {Proceedings of the 7th {International} {Conference} on {Intelligent} {Technologies} for {Interactive} {Entertainment}},
publisher = {IEEE},
author = {Repetto, Andrea and Catalano, Chiara Eva},
year = {2015},
file = {Repetto_Catalano_2015_A_Semantic_Layer_for_Knowledge-Based_Game_Design_in_Edutainment_Applications.pdf:files/5835/Repetto_Catalano_2015_A_Semantic_Layer_for_Knowledge-Based_Game_Design_in_Edutainment_Applications.pdf:application/pdf},
}
@article{gold_neural_2007,
title = {The {Neural} {Basis} of {Decision} {Making}},
volume = {30},
issn = {0147-006X, 1545-4126},
url = {http://www.annualreviews.org/doi/10.1146/annurev.neuro.29.051605.113038},
doi = {10.1146/annurev.neuro.29.051605.113038},
abstract = {The study of decision making spans such varied fields as neuroscience, psychology, economics, statistics, political science, and computer science. Despite this diversity of applications, most decisions share common elements including deliberation and commitment. Here we evaluate recent progress in understanding how these basic elements of decision formation are implemented in the brain. We focus on simple decisions that can be studied in the laboratory but emphasize general principles likely to extend to other settings.},
language = {en},
number = {1},
urldate = {2020-11-03},
journal = {Annual Review of Neuroscience},
author = {Gold, Joshua I. and Shadlen, Michael N.},
month = jul,
year = {2007},
note = {Number: 1},
pages = {535--574},
file = {Gold_Shadlen_2007_The_Neural_Basis_of_Decision_Making.pdf:files/5778/Gold_Shadlen_2007_The_Neural_Basis_of_Decision_Making.pdf:application/pdf},
}
@article{bogacz_optimal_2007,
title = {Optimal decision-making theories: linking neurobiology with behaviour},
volume = {11},
issn = {13646613},
shorttitle = {Optimal decision-making theories},
url = {https://linkinghub.elsevier.com/retrieve/pii/S1364661307000290},
doi = {10.1016/j.tics.2006.12.006},
language = {en},
number = {3},
urldate = {2020-11-03},
journal = {Trends in Cognitive Sciences},
author = {Bogacz, Rafal},
month = mar,
year = {2007},
note = {Number: 3},
pages = {118--125},
file = {Bogacz_2007_Optimal_decision-making_theories.pdf:files/5783/Bogacz_2007_Optimal_decision-making_theories.pdf:application/pdf},
}
@incollection{romero_creacube_2019,
address = {Cham},
title = {{CreaCube}, a {Playful} {Activity} with {Modular} {Robotics}},
volume = {11385},
isbn = {978-3-030-11547-0 978-3-030-11548-7},
url = {http://link.springer.com/10.1007/978-3-030-11548-7_37},
abstract = {Programmable toys are blurring the lines between serious games and educational robotics solutions. In this study, the CreaCube activity is analysed using Cubelets modular robotics based on the Learning Mechanics and Game Mechanics (LMGM) framework. The CreaCube playful activity is used to analyse the creative problem-solving process through a playful activity made from interconnectable electronic cubes. The resolution of the CreaCube activity involves the manipulation and assembly of cubes to build a vehicle that moves independently from an initial point to a final point. After describing the CreaCube activity from the perspective of the LMGM framework, the discussion is developed in relation to creative problem solving.},
language = {en},
urldate = {2020-11-03},
booktitle = {Games and {Learning} {Alliance}},
publisher = {Springer International Publishing},
author = {Romero, Margarida and David, Dayle and Lille, Benjamin},
editor = {Gentile, Manuel and Allegra, Mario and Söbke, Heinrich},
year = {2019},
doi = {10.1007/978-3-030-11548-7_37},
note = {Series Title: Lecture Notes in Computer Science},
pages = {397--405},
annote = {Series Title: Lecture Notes in Computer Science},
file = {Romero_et_al_2019_CreaCube,_a_Playful_Activity_with_Modular_Robotics.pdf:files/5770/Romero_et_al_2019_CreaCube,_a_Playful_Activity_with_Modular_Robotics.pdf:application/pdf},
}
@incollection{oudeyer_intrinsic_2016,
series = {Motivation},
title = {Intrinsic motivation, curiosity, and learning: {Theory} and applications in educational technologies},
volume = {229},
isbn = {978-0-444-63701-7},
shorttitle = {Intrinsic motivation, curiosity, and learning},
url = {https://linkinghub.elsevier.com/retrieve/pii/S0079612316300589},
abstract = {This chapter studies the bidirectional causal interactions between curiosity and learning and discusses how understanding these interactions can be leveraged in educational technology applications. First, we review recent results showing how state curiosity, and more generally the experience of novelty and surprise, can enhance learning and memory retention. Then, we discuss how psychology and neuroscience have conceptualized curiosity and intrinsic motivation, studying how the brain can be intrinsically rewarded by novelty, complexity, or other measures of information. We explain how the framework of computational reinforcement learning can be used to model such mechanisms of curiosity. Then, we discuss the learning progress (LP) hypothesis, which posits a positive feedback loop between curiosity and learning. We outline experiments with robots that show how LP-driven attention and exploration can self-organize a developmental learning curriculum scaffolding efficient acquisition of multiple skills/tasks. Finally, we discuss recent work exploiting these conceptual and computational models in educational technologies, showing in particular how intelligent tutoring systems can be designed to foster curiosity and learning.},
language = {eng},
booktitle = {Progress in {Brain} {Research}},
publisher = {Elsevier},
author = {Oudeyer, P.-Y. and Gottlieb, J. and Lopes, M.},
year = {2016},
doi = {10.1016/bs.pbr.2016.05.005},
keywords = {Learning, Neuroscience, Animals, Humans, Education, Educational technology, Active learning, Active teaching, Artificial intelligence, Curiosity, Educational Technology, Exploratory Behavior, Feedback, Psychological, Intrinsic motivation, Motivation, Psychological Theory, Computational modelling},
pages = {257--284},
annote = {Extracted Annotations (3/7/2021, 3:58:49 PM)
"activities or stimuli that are surprising, novel, of intermediate complexity, or characterized by a knowledge gap or by errors in prediction" (Oudeyer, et and al 2016:258)
"collative variables" (Oudeyer, et and al 2016:258)
"TD learning" (Oudeyer, et and al 2016:259)
"organisms only learn when events violate their expectations" (Oudeyer, et and al 2016:259)
"forms of intrinsic motivation motivate the organism to search for information and competence gain." (Oudeyer, et and al 2016:259)
"reward-related dopaminergic circuits can be activated by information independently of extrinsic reward" (Oudeyer, et and al 2016:259)
"improve learning efficiency by self-organizing developmental learning trajectories" (Oudeyer, et and al 2016:259)
"Drives to manipulate, drives to explore" (Oudeyer, et and al 2016:260)
"hunger or pain." (Oudeyer, et and al 2016:260)
"not a consummatory response to a stressful perturbation of the organism's body" (Oudeyer, et and al 2016:260)
"Reduction of cognitive dissonance" (Oudeyer, et and al 2016:260)
"reduce dissonance, defined as an incompatibility between internal cognitive structures and the situations currently perceived" (Oudeyer, et and al 2016:260)
"spontaneous exploration behaviours which increase uncertainty" (Oudeyer, et and al 2016:261)
"Optimal incongruity." (Oudeyer, et and al 2016:261)
"most rewarding situations were those with an intermediate level of novelty," (Oudeyer, et and al 2016:261)
"Motivation for competence" (Oudeyer, et and al 2016:261)
"what motivates people is the degree of control they can have on other people, external objects and themselves" (Oudeyer, et and al 2016:261)
"brain could be intrinsically rewarded by experiencing information gain, novelty or complexity" (Oudeyer, et and al 2016:262)
"whether one could identify actual neural circuitry linking the detection of novelty with the brain reward system" (Oudeyer, et and al 2016:262)
"novelty may be associated with positive or with negative outcomes, and thus learn to avoid novelty when their associated outcome is negative" (Oudeyer, et and al 2016:264)
"intermediate novelty" (Oudeyer, et and al 2016:265)
"intermediate" appears difficult to define precisely," (Oudeyer, et and al 2016:265)
"no guarantee that observing a novel or intermediate complexity stimulus provides information that can improve the organism's prediction and control in the world" (Oudeyer, et and al 2016:265)
"the organism loses interest in activities that are too easy or too difficult to predict (i.e. where uncertainty is low or where uncertainty is high but not reducible), and focuses specifically on learnable activities that are just beyond its current predictive capacities" (Oudeyer, et and al 2016:265)
"an explicit measure of intermediate complexity is not computed by this mechanism: it is an emergent property" (Oudeyer, et and al 2016:265)
"the brain would be motivated to search for (intermediate) novelty or complexity" (Oudeyer, et and al 2016:266)
"experiencing learning in a given activity (rather than just intermediate novelty) triggers an intrinsic reward" (Oudeyer, et and al 2016:266)
"positive feedback loop" (Oudeyer, et and al 2016:267)
"complex learning dynamics selforganizing learning curriculum with phases of increasing complexity" (Oudeyer, et and al 2016:267)},
file = {Oudeyer_et_al_2016_Intrinsic_motivation,_curiosity,_and_learning.pdf:files/5772/Oudeyer_et_al_2016_Intrinsic_motivation,_curiosity,_and_learning.pdf:application/pdf;ScienceDirect Snapshot:files/6801/S0079612316300589.html:text/html},
}
@article{alexandre_les_2020,
title = {Les relations difficiles entre l'{Intelligence} {Artificielle} et les {Neurosciences}},
url = {https://hal.inria.fr/hal-02925517},
abstract = {L'Intelligence Artificielle (IA) s'est construite sur une opposition forte entre connaissances et données. Les neurosciences ont tout d'abord fourni des éléments confortant cette vision avec la description de deux formes de mémoire, traitant respectivement de connaissances et de données. Les neurosciences ont ensuite décrit des interactions fortes entre ces deux formes de mémoire et ont suggéré que ces interactions permettent une cognition plus robuste et plus performante. De son coté, l'IA a pâti des limitations résultant de la dualité stricte entre connaissances et données. Pour autant, les chercheurs en IA restent trop souvent bloqués sur ces conceptions initiales et peinent à intégrer les mécanismes suggérés par les neurosciences. Ils se privent ainsi de pistes d'évolution prometteuses et d'un dialogue fertile avec ce domaine.},
language = {fr},
urldate = {2020-10-05},
journal = {Interstices},
author = {Alexandre, Frédéric},
month = aug,
year = {2020},
annote = {NOTES
mémoire explicite (ou déclarative) ={\textgreater} manipuler des connaissances
={\textgreater} IA symbolique, ontologies, systèmes experts (bases de règles)
ex : repas d’hier soir (mémoire épisodique) ou avoir la connaissance que le ciel est bleu (mémoire sémantique)
={\textgreater} hippocampe + lobe temporal médial
\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_
mémoire implicite (non déclarative) ={\textgreater} acquérir une compétence à partir d’expériences multiples (assimilables à des données)
={\textgreater} IA numérique, data science, réseaux de neurones
ex: langue maternelle (apprise par la pratique), faire du vélo (mémoire procédurale).
={\textgreater} ganglions de la base + cortex
\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_
échanges entre ces mémoires :
consolidation, formation des habitudes.
\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_
consolidation = transfert hippocampe -{\textgreater} cortex (sommeil)
apprentissage lent de la mémoire procédurale dans le cortex (couches successives de neurones) : attention à l'oubli catastrophique !
vs
formation rapide de la mémoire épisodique dans l’hippocampe (réseaux récurrents ={\textgreater} mémoire des configurations + codage clairsemé) : attention au stockage et aux interférences !
formation d'un nvelle mémoire sémantique commune
\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_
formation des habitudes
2 modes de prise de décision :
- réflexif (reflexes, behavioristes)
- réflectif (reflexion, cognitivistes)
dégagement de régularités ={\textgreater} formation d'associations stimulus-action
sans représentation explicite du but
\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_
Remarques :
- l'hippocampe est en fait alimenté presque exclusivement par des représentations provenant du cortex, donc correspondant à l’état courant de la mémoire implicite, ce qui indique que ces deux mémoires sont en fait interdépendantes et co-construites.
- automatisation révisable
},
file = {Alexandre_2020_Les_relations_difficiles_entre_l'Intelligence_Artificielle_et_les_Neurosciences.pdf:files/5856/Alexandre_2020_Les_relations_difficiles_entre_l'Intelligence_Artificielle_et_les_Neurosciences.pdf:application/pdf;Snapshot:files/5855/hal-02925517.html:text/html},
}
@article{romero_line-mnemosyne_2020,
title = {{LINE}-{Mnémosyne} : {Des} neurosciences computationnelles aux sciences de l’éducation computationnelles pour la modélisation du cerveau de l’apprenant et du contexte de l’activité d’apprentissage},
shorttitle = {{LINE} - {Mnémosyne}},
url = {https://hal.inria.fr/hal-02541099},
abstract = {Face au défi de comprendre les processus d’apprentissage humain, notre programme de recherche interdisciplinaire vise donc à combiner d’une part des modélisations développée en neurosciences computationnelles et en intelligence artificielle bio-inspirée et d’autre part la modélisation en sciences de l’éducation de la personne apprenante et la situation d’apprentissage dans une tâche bien définie. Ce programme doit contribuer aux travaux initiés dans ce domaine émergent des sciences computationnelles de l’éducation (Computational Learning Sciences).},
language = {fr},
number = {108},
urldate = {2020-10-05},
journal = {Bulletin de l'Association Française pour l'Intelligence Artificielle},
author = {Romero, Margarida and Alexandre, Frédéric and Viéville, Thierry and Giraudon, Gérard},
month = apr,
year = {2020},
file = {Romero_et_al_2020_LINE-Mnemosyne.pdf:files/5769/Romero_et_al_2020_LINE-Mnemosyne.pdf:application/pdf;Snapshot:files/5793/hal-02541099.html:text/html},
}
@article{wang_learning_2017,
title = {Learning to reinforcement learn},
url = {http://arxiv.org/abs/1611.05763},
abstract = {In recent years deep reinforcement learning (RL) systems have attained superhuman performance in a number of challenging task domains. However, a major limitation of such applications is their demand for massive amounts of training data. A critical present objective is thus to develop deep RL methods that can adapt rapidly to new tasks. In the present work we introduce a novel approach to this challenge, which we refer to as deep meta-reinforcement learning. Previous work has shown that recurrent networks can support meta-learning in a fully supervised context. We extend this approach to the RL setting. What emerges is a system that is trained using one RL algorithm, but whose recurrent dynamics implement a second, quite separate RL procedure. This second, learned RL algorithm can differ from the original one in arbitrary ways. Importantly, because it is learned, it is configured to exploit structure in the training domain. We unpack these points in a series of seven proof-of-concept experiments, each of which examines a key aspect of deep meta-RL. We consider prospects for extending and scaling up the approach, and also point out some potentially important implications for neuroscience.},
language = {en},
urldate = {2020-10-01},
journal = {arXiv:1611.05763 [cs, stat]},
author = {Wang, Jane X. and Kurth-Nelson, Zeb and Tirumala, Dhruva and Soyer, Hubert and Leibo, Joel Z. and Munos, Remi and Blundell, Charles and Kumaran, Dharshan and Botvinick, Matt},
month = jan,
year = {2017},
note = {arXiv: 1611.05763},
keywords = {Statistics - Machine Learning, Artificial intelligence, Machine Learning},
annote = {Comment: 17 pages, 7 figures, 1 table},
annote = {NOTES
Bandits:
dependent bandits: the system learned to take advantage of the task’s covariance structure
MDPs:
2-step task
the learning procedure that emerges from meta-RL can differ starkly from the original RL algorithm used to train the network weights, and takes a form that exploits consistent task structure.
a system trained using a model-free RL algorithm can develop behavior that emulates model-based control.
Harlow’s animal learning taskthe recurrent network learned to exploit the task’s structure in order to displayone-shot learning with complex novel stimuli
CONCLUSION
Deep meta-RL involves a combination of three ingredients:
(1) Use of a deep RL algorithm to train a recurrent neural network,
(2) a training set that includes a series of interrelated tasks,
(3) network input that includes the action selected and reward received in the previous time interval.},
file = {Wang_et_al_2017_Learning_to_reinforcement_learn.pdf:files/5823/Wang_et_al_2017_Learning_to_reinforcement_learn.pdf:application/pdf},
}
@article{wang_prefrontal_2018,
title = {Prefrontal cortex as a meta-reinforcement learning system},
volume = {21},
issn = {1097-6256, 1546-1726},
url = {http://www.nature.com/articles/s41593-018-0147-8},
doi = {10.1038/s41593-018-0147-8},
language = {en},
number = {6},
urldate = {2020-10-01},
journal = {Nature Neuroscience},
author = {Wang, Jane X. and Kurth-Nelson, Zeb and Kumaran, Dharshan and Tirumala, Dhruva and Soyer, Hubert and Leibo, Joel Z. and Hassabis, Demis and Botvinick, Matthew},
month = jun,
year = {2018},
note = {Number: 6},
pages = {860--868},
file = {Wang_et_al_2018_Prefrontal_cortex_as_a_meta-reinforcement_learning_system.pdf:files/5767/Wang_et_al_2018_Prefrontal_cortex_as_a_meta-reinforcement_learning_system.pdf:application/pdf},
}
@article{singh_intrinsically_2010,
title = {Intrinsically {Motivated} {Reinforcement} {Learning}: {An} {Evolutionary} {Perspective}},
volume = {2},
issn = {1943-0604, 1943-0612},
shorttitle = {Intrinsically {Motivated} {Reinforcement} {Learning}},
url = {http://ieeexplore.ieee.org/document/5471106/},
doi = {10.1109/TAMD.2010.2051031},
abstract = {There is great interest in building intrinsic motivation into artificial systems using the reinforcement learning framework. Yet, what intrinsic motivation may mean computationally, and how it may differ from extrinsic motivation, remains a murky and controversial subject. In this paper, we adopt an evolutionary perspective and define a new optimal reward framework that captures the pressure to design good primary reward functions that lead to evolutionary success across environments. The results of two computational experiments show that optimal primary reward signals may yield both emergent intrinsic and extrinsic motivation. The evolutionary perspective and the associated optimal reward framework thus lead to the conclusion that there are no hard and fast features distinguishing intrinsic and extrinsic reward computationally. Rather, the directness of the relationship between rewarding behavior and evolutionary success varies along a continuum.},
language = {en},
number = {2},
urldate = {2020-11-05},
journal = {IEEE Transactions on Autonomous Mental Development},
author = {Singh, Satinder and Lewis, Richard L. and Barto, Andrew G. and Sorg, Jonathan},
month = jun,
year = {2010},
pages = {70--82},
file = {Singh_et_al_2010_Intrinsically_Motivated_Reinforcement_Learning.pdf:files/5826/Singh_et_al_2010_Intrinsically_Motivated_Reinforcement_Learning.pdf:application/pdf},
}
@article{simon_functional_1975,
title = {The functional equivalence of problem solving skills},
volume = {7},
issn = {0010-0285},
url = {http://www.sciencedirect.com/science/article/pii/0010028575900122},
doi = {10.1016/0010-0285(75)90012-2},
abstract = {The tower of Hanoi problem is used to show that, even in simple problem environments, numerous distinct solution strategies are available, and different subjects may learn different strategies. Four major classes of solution strategies are described for the problem. Different strategies have different degrees of transferability, place different burdens on short-term memory and on perception, and require different learning processes for their acquisition. The analysis underscores the importance of subject-by-subject analysis of “what is learned” in understanding human behavior in problem-solving situations, and provides a technique for describing subjects' task performance programs in detail.},
language = {en},
number = {2},
urldate = {2020-11-05},
journal = {Cognitive Psychology},
author = {Simon, Herbert A},
month = apr,
year = {1975},
pages = {268--288},
file = {ScienceDirect Snapshot:files/5830/0010028575900122.html:text/html;Simon_1975_The_functional_equivalence_of_problem_solving_skills.pdf:files/5829/Simon_1975_The_functional_equivalence_of_problem_solving_skills.pdf:application/pdf},
}
@article{simon_optimal_1975,
title = {Optimal problem-solving search: {All}-or-none solutions},
volume = {6},
issn = {0004-3702},
shorttitle = {Optimal problem-solving search},
url = {http://www.sciencedirect.com/science/article/pii/0004370275900028},
doi = {10.1016/0004-3702(75)90002-8},
abstract = {Optimal algorithms are derived for satisficing problem-solving search, that is, search where the goal is to reach any solution, no distinction being made among different solutions. This task is quite different from search for best solutions or shortest path solutions. Constraints may be placed on the order in which sites may be searched. This paper treats satisficing searches through partially ordered search spaces where there are multiple alternative goals.},
language = {en},
number = {3},
urldate = {2020-11-05},
journal = {Artificial Intelligence},
author = {Simon, Herbert A. and Kadane, Joseph B.},
month = sep,
year = {1975},
pages = {235--247},
file = {ScienceDirect Snapshot:files/5828/0004370275900028.html:text/html;Simon_Kadane_1975_Optimal_problem-solving_search.pdf:files/5827/Simon_Kadane_1975_Optimal_problem-solving_search.pdf:application/pdf},
}
@phdthesis{donoso_cerveau_2013,
type = {{PhD} {Thesis}},
title = {Le cerveau stratège : les fondements du raisonnement dans le cortex préfrontal humain},
url = {http://www.theses.fr/2013PA066535},
author = {Donoso, Maël},
year = {2013},
keywords = {Prise de décision, Cortex cérébral, Imagerie par résonance magnétique},
annote = {Extracted Annotations (12/10/2021, 5:09:41 PM)
"Le modèle MMBRL ne définit pas explicitement comment les différents modules monitorés sont apparus, et le modèle de Yu et Dayan ne fait aucune hypothèse, lorsque le task-‐set par défaut est abandonné, sur les mécanismes qui permettent à un nouveau task-‐set par défaut d'émerger. Aucun d'entre eux ne permet donc d'appréhender la dynamique du raisonnement, qui intègre certes l'évaluation et la sélection, mais également la création d'options, nécessaire face à un environnement incertain dont les contingences sont en perpétuelle évolution" (Donoso 2013:46)
"le problème de la créativité et de la validation de nouveaux task-‐sets est résolue par la notion de test d'hypothèse, qui permet au modèle de créer un task-‐set provisoire, le task-‐set « probe », de l'intégrer définitivement en mémoire de travail si sa confiance dépasse le seuil de 50\%, et de le supprimer dans le cas contraire." (Donoso 2013:46)},
annote = {Note de Fred:
à lire avant le papier de collins à mon avis
-le modèle est dans le chapitre 3 (p93-102)
-mais les deux premiers chapitres sont intéressants pour votre culture générale et pour mieux comprendre PROBE
-par contre après la p. 103, ce n'est pas forcément utile (mais si vous êtes curieux de savoir la fin...)
donc à mon avis lire jusque p102, c'est très bien
},
annote = {PROBE
Main idea: task-sets, action-sets
Proposes a task-switching model
Continuity of:
- MMBRL
- Yu \& Dayan (2005, 2006): role of neuroadrenaline in task switching
Extracted Annotations (4/28/2021, 10:32:26 AM)
"Le modèle MMBRL ne définit pas explicitement comment les différents modules monitorés sont apparus, et le modèle de Yu et Dayan ne fait aucune hypothèse, lorsque le task-‐set par défaut est abandonné, sur les mécanismes qui permettent à un nouveau task-‐set par défaut d'émerger. Aucun d'entre eux ne permet donc d'appréhender la dynamique du raisonnement, qui intègre certes l'évaluation et la sélection, mais également la création d'options, nécessaire face à un environnement incertain dont les contingences sont en perpétuelle évolution" (Donoso 2013:46)
"le problème de la créativité et de la validation de nouveaux task-‐sets est résolue par la notion de test d'hypothèse, qui permet au modèle de créer un task-‐set provisoire, le task-‐set « probe », de l'intégrer définitivement en mémoire de travail si sa confiance dépasse le seuil de 50\%, et de le supprimer dans le cas contraire." (Donoso 2013:46)},
file = {Donoso_2013_Le_cerveau_stratege.pdf:files/5795/Donoso_2013_Le_cerveau_stratege.pdf:application/pdf;PROBE.png:files/6344/PROBE.png:image/png},
}
@article{domenech_executive_2015,
title = {Executive control and decision-making in the prefrontal cortex},
volume = {1},
issn = {23521546},
url = {https://linkinghub.elsevier.com/retrieve/pii/S2352154614000278},
doi = {10.1016/j.cobeha.2014.10.007},
language = {en},
urldate = {2020-11-06},
journal = {Current Opinion in Behavioral Sciences},
author = {Domenech, Philippe and Koechlin, Etienne},
month = feb,
year = {2015},
pages = {101--106},
file = {Domenech_Koechlin_2015_Executive_control_and_decision-making_in_the_prefrontal_cortex.pdf:files/5777/Domenech_Koechlin_2015_Executive_control_and_decision-making_in_the_prefrontal_cortex.pdf:application/pdf},
}
@article{collins_reasoning_2012,
title = {Reasoning, {Learning}, and {Creativity}: {Frontal} {Lobe} {Function} and {Human} {Decision}-{Making}},
volume = {10},
issn = {1545-7885},
shorttitle = {Reasoning, {Learning}, and {Creativity}},
url = {https://dx.plos.org/10.1371/journal.pbio.1001293},
doi = {10.1371/journal.pbio.1001293},
abstract = {The frontal lobes subserve decision-making and executive control—that is, the selection and coordination of goal-directed behaviors. Current models of frontal executive function, however, do not explain human decision-making in everyday environments featuring uncertain, changing, and especially open-ended situations. Here, we propose a computational model of human executive function that clarifies this issue. Using behavioral experiments, we show that unlike others, the proposed model predicts human decisions and their variations across individuals in naturalistic situations. The model reveals that for driving action, the human frontal function monitors up to three/four concurrent behavioral strategies and infers online their ability to predict action outcomes: whenever one appears more reliable than unreliable, this strategy is chosen to guide the selection and learning of actions that maximize rewards. Otherwise, a new behavioral strategy is tentatively formed, partly from those stored in long-term memory, then probed, and if competitive confirmed to subsequently drive action. Thus, the human executive function has a monitoring capacity limited to three or four behavioral strategies. This limitation is compensated by the binary structure of executive control that in ambiguous and unknown situations promotes the exploration and creation of new behavioral strategies. The results support a model of human frontal function that integrates reasoning, learning, and creative abilities in the service of decision-making and adaptive behavior.},
language = {en},
number = {3},
urldate = {2020-11-06},
journal = {PLoS Biology},
author = {Collins, Anne and Koechlin, Etienne},
editor = {O'Doherty, John P.},
month = mar,
year = {2012},
keywords = {Learning, Reliability, Decision making, Entropy, Human learning, Human performance, Long term memory, Sensory cues},
pages = {e1001293},
file = {Collins_Koechlin_2012_Reasoning,_Learning,_and_Creativity.pdf:files/6811/Collins_Koechlin_2012_Reasoning,_Learning,_and_Creativity.pdf:application/pdf;Snapshot:files/6812/article.html:text/html},
}
@incollection{miller_realigning_2018,
title = {Realigning {Models} of {Habitual} and {Goal}-{Directed} {Decision}-{Making}},
isbn = {978-0-12-812098-9},
url = {http://www.sciencedirect.com/science/article/pii/B9780128120989000188},
abstract = {The classic dichotomy between habitual and goal-directed behavior is often mapped onto a dichotomy between model-free and model-based reinforcement learning (RL) algorithms, putatively implemented in segregated neuronal circuits. Despite significant heuristic value in motivating experimental investigations, several lines of evidence suggest that this mapping is in need of modification and/or realignment. First, whereas habitual and goal-directed behaviors have been shown to depend on cleanly separable neural circuitry, recent data suggest that model-based and model-free representations in the brain are largely overlapping. Second, habitual behaviors need not involve representations of expected reinforcement (i.e., need not involve RL, model-free, or otherwise) but may be based instead on simple stimulus–response associations. Finally, goal-directed decisions may not reflect a single model-based algorithm but rather a continuum of “model-basedness.” These lines of evidence thus suggest a possible reconceptualization of the distinction between model-free versus model-based RL—one in which both contribute to a single goal-directed system that is value-based, as opposed to distinct, habitual mechanisms that are value-free. In this chapter, we discuss new models that have extended the RL approach to modeling habitual and goal-directed behavior and assess how these have clarified our understanding of the underlying neural circuitry.},
language = {en},
urldate = {2020-11-13},
booktitle = {Goal-{Directed} {Decision} {Making}},
publisher = {Academic Press},
author = {Miller, Kevin J. and Ludvig, Elliot A. and Pezzulo, Giovanni and Shenhav, Amitai},
editor = {Morris, Richard and Bornstein, Aaron and Shenhav, Amitai},
month = jan,
year = {2018},
doi = {10.1016/B978-0-12-812098-9.00018-8},
keywords = {Model-based, Model-free, Reinforcement learning},
pages = {407--428},
annote = {Extracted Annotations (12/10/2021, 5:10:49 PM)
"habitual and goal-directed behaviors have been shown to depend on cleanly separable neural circuitry, recent data suggest that model-based and model-free representations in the brain are largely overlapping" (Miller, et and al 2018:407)
"habitual behaviors" (Miller, et and al 2018:407)
"need not involve RL" (Miller, et and al 2018:407)
"stimulus-response associations" (Miller, et and al 2018:407)
"goal-directed decisions may not reflect a single model-based algorithm but rather a continuum of "model-basedness"" (Miller, et and al 2018:407)
"both contribute to a single goal-directed system that is value-based, as opposed to distinct, habitual mechanisms that are value-free" (Miller, et and al 2018:407)
"distinguished from habits by its sensitivity to context (including motivational state), future outcomes, and the means-end relationship between the actions being pursued and the rewarding outcome expected as a result" (Miller, et and al 2018:408)
"goal-directed" (Miller, et and al 2018:408)
"dissociable patterns of neural activity" (Miller, et and al 2018:408)
"inactivation studies showing that behavior can be made more habitual or goal-directed by selectively inactivating specific regions of striatum and prefrontal cortex" (Miller, et and al 2018:408)
"abitual" (Miller, et and al 2018:408)
"habits form through repetition of prior actions, espectivef whether those actions were positively reinforced" (Miller, et and al 2018:409)
"habits may be alue-free" (Miller, et and al 2018:409)
"model-free and model-based RL processes have tended to recruit largely overlapping circuits" (Miller, et and al 2018:409)
"the links between the animal and machine learning taxonomies are at the very least incomplete if not deeply misaligned" (Miller, et and al 2018:409)
"belief-free" (Miller, et and al 2018:410)
"belief-based" (Miller, et and al 2018:410)
"the role that value does or does not play in driving those behaviors" (Miller, et and al 2018:410)
"this perseverative system considers all past actions, whether they were taken under its control or under the control of the goal-directed system" (Miller, et and al 2018:410)
"Hebbian plasticity" (Miller, et and al 2018:410)
"probabilities reverse" (Miller, et and al 2018:411)
"Action A is initially reinforced" (Miller, et and al 2018:411)
"The weight of the goal-directed controller gradually decreases as habits strengthen, then increases post-reversal as the global and goal-directed reinforcement rates diverge" (Miller, et and al 2018:411)
"belief-freechemes" (Miller, et and al 2018:411)
"selects actions based on stimuli" (Miller, et and al 2018:411)
"elief-basedchemes" (Miller, et and al 2018:411)
"internal" (Miller, et and al 2018:411)
"estimates" (Miller, et and al 2018:411)
"important when the environment is partially observable" (Miller, et and al 2018:411)
"A belief-free agent, who has no notion of state or context, would select a policy to go directly to one of the two reward sites" (Miller, et and al 2018:412)
""epistemic action"" (Miller, et and al 2018:412)
"A belief-based agent, who knows it is uncertain about the context and that the cue will reduce this uncertainty, would instead go to the cue location first" (Miller, et and al 2018:412)
"a belief-free scheme is sufficient to characterize habitual systems" (Miller, et and al 2018:413)
"with no residual uncertainty about the current context, the agent no longer needs a belief-based scheme or epistemic actions" (Miller, et and al 2018:413)
"the belief-free scheme uses stimulusresponse mechanisms and has no notion of value." (Miller, et and al 2018:413)
"from sensory measurements" (Miller, et and al 2018:414)
"credit assignment problem" (Miller, et and al 2018:414)
"infers its state" (Miller, et and al 2018:414)
"stochastic" (Miller, et and al 2018:414)
"aliasing" (Miller, et and al 2018:414)
"aliasing) is more difficult to handle" (Miller, et and al 2018:414)
"Belief-MDP" (Miller, et and al 2018:414)
"distinguished on the basis of a trace of previous observations" (Miller, et and al 2018:414)
"Partially Observable Markov Decision Process" (Miller, et and al 2018:414)
"Kalman (or Bayesian) filters" (Miller, et and al 2018:414)
"distinct forms of memory for past rewards: a slowly-updating, long-term memory and a rapidly-adjusting short-term memory" (Miller, et and al 2018:414)
"ills" (Miller, et and al 2018:414)
"flexible responding, analogous to goal-directed control." (Miller, et and al 2018:415)
"optimal model-based control is impossible in realistic environments, because it would require enumerating and evaluating the full tree of possible future states" (Miller, et and al 2018:415)
"approximate" (Miller, et and al 2018:415)
"random" (Miller, et and al 2018:415)
"heuristics" (Miller, et and al 2018:415)
"explore only parts of the search tree," (Miller, et and al 2018:415)
"DYNA," (Miller, et and al 2018:415)
"predictive state representation" (Miller, et and al 2018:415)
"no explicit planning takes place" (Miller, et and al 2018:415)
""model-basedness" itself forms a continuous dimension that varies in informational richness" (Miller, et and al 2018:416)
"the kind of action an animal takes after experiencing a degradation of contingencies or devaluation of outcomes following extended training" (Miller, et and al 2018:416)
"faster and more accurate" (Miller, et and al 2018:416)
"inflexibility of habitual control trades off with gains in speed and consistency of action." (Miller, et and al 2018:416)
"cognitive control." (Miller, et and al 2018:417)
"increasingly goal-directed decisions are slower, more susceptible to interference from other ongoing processes, and are experienced as costly/effortful" (Miller, et and al 2018:417)
"goal-directed decision-making requires searching through an internal map of potential future states in order to identify the best possible future state" (Miller, et and al 2018:417)
"selection from and maintenance of episodic and semantic memories, as well as instantiation of relevant contexts" (Miller, et and al 2018:417)
"behavior begins under putatively goal-directed control, then over time becomes habitual" (Miller, et and al 2018:417)
"Do we need model-free" (Miller, et and al 2018:418)
"Historically, the strongest support for model-free algorithms in the brain has come from a series of seminal studies demonstrating that firing rates of dopaminergic neurons in the midbrain showa response pattern evocative of the "prediction error" signal" (Miller, et and al 2018:418)
"This picture has been complicated by recent evidence indicating that dopamine transients may be informed by model-based information" (Miller, et and al 2018:418)
"prediction errors that are consistent with inference" (Miller, et and al 2018:418)
"information about both real and counterfactual rewards" (Miller, et and al 2018:418)
"prediction errors indicative of model-based" (Miller, et and al 2018:418)
"they even respond to errors in the predictions of sensory features that do not impact the value of the reward received" (Miller, et and al 2018:418)
"dopamine plays a role in model-based rather than model-free control." (Miller, et and al 2018:418)
"dopamine may not be involved in specifically model-free computations," (Miller, et and al 2018:419)
"these developments raise doubts about the widely accepted notion that the brain implements model-free reinforcement learning algorithms," (Miller, et and al 2018:419)
"distinct processes associated with goal-directed control, including commiting to a goal Oettingen 2012) formulating a plan to achieve that goal Wieber and Gollwitzer 2017) pursuing that plan in the face of unexpected circumstances Gollwitzer and Oettingen 2012) and learning from one's success or failure to achieve the desired goal" (Miller, et and al 2018:419)
"proposing that goa" (Miller, et and al 2018:419)
"goal selection and goal pursuit map to two distinct computational processes with separated demands and neural underpinnings" (Miller, et and al 2018:419)
"computational psychiatry" (Miller, et and al 2018:419)
"real-life situations requires some form of approximation" (Miller, et and al 2018:419)
"abstraction, modularization and/or hierarchization." (Miller, et and al 2018:419)
"aspects of goal-directed and habitual control would plausibly need to be continuously and creatively meshed." (Miller, et and al 2018:420)
"hierarchical reinforcement learning," (Miller, et and al 2018:420)
""options"" (Miller, et and al 2018:420)
"compete for control of behavior, with an arbitration mechanism that allocates control to one or another mechanism" (Miller, et and al 2018:420)
"in parallel," (Miller, et and al 2018:420)
"habits can be activated by goal-directed mechanisms" (Miller, et and al 2018:420)
"hierarchical organization." (Miller, et and al 2018:420)
"goals themselves may be activated by habits" (Miller, et and al 2018:421)
"goal-directed and habitual behavior interact by forming part of a single controller, thereby cooperating to create a single integrated value" (Miller, et and al 2018:421)
"closely related to the DYNA architecture" (Miller, et and al 2018:421)
"continuum" (Miller, et and al 2018:421)
"hierarchical predictive coding" (Miller, et and al 2018:421)
""mixed instrumental controller"" (Miller, et and al 2018:421)
"the more samples are drawn from the internal model, the more behavior will appear to be planned rather than model-free." (Miller, et and al 2018:421)
"explicit arbiter that assigns weights adaptively" (Miller, et and al 2018:421)
"Habitual behavior arises when lower layers acquire sufficient precision (a measure of inverse uncertainty in predictive coding) and become essentially insensitive to top-down messages." (Miller, et and al 2018:421)
"the continuum between goal-directed and habitual behavior depends on the relative strength (precision) of the top-down and bottom-up messages (predictions) in the hierarchical architecture, without an explicit arbiter." (Miller, et and al 2018:421)
"The majority of these schemes were developed in the context of models which assert that habitual behavior relies on model-free mechanisms, and may be best suited to understanding the interactions between model-based and model-free control within the goal-directed system" (Miller, et and al 2018:421)
"model-based/model-free dichotomy may not map cleanly onto neural circuitry," (Miller, et and al 2018:422)
"new behavioral measures" (Miller, et and al 2018:422)},
annote = {Notes
Abstract
Habitual and goal-directed DO depend on separable circuits.BUT MB and MF are overlapping
Habitual behaviour is not necessarily RL (can be simple S-R association)
Goal-directed decisions may not reflect a single MB algo, but rather a continuum of MB-ness
Mine:
There may not be MF RL at all in the brain
Body
Habits form through repetition of prior actions, irrespective of whether those actions were positively reinforced. Habits may be value-free.
"The links between the animal (habitual/goal-directed) and ML (MF/MB) taxonomies are at the very least incomplete if not deeply misaligned"
habit system learns all the time, behaviour can then be "passed on" from the goal-directed system to the habitual. =cortical hebbian learning like in Aubin (2016) or Boraud (\& Rougier) (2018)
Belief-free/belief-based. Forming beliefs is helpful to infer states when not directly observable.
Belief-MDP solves the problem of aliasing (an agent cannot infer true state from obs because different states can be rewarded/look the same) by using a trace of previous observations for state inference
Partially observable MDP uses bayesian/kalman filters to infer states
Epistemic action (as opposed to pragmatic): aims at changing the agent's belief state in uncertain environment (e.g. get a cue) and not achieving an external goal
Friston et al. 2016 propose that a belief-free scheme is sufficient to characterize habitual systems, but that a belief-based scheme is necessary to characterize goal-directed systems
MB is infeasible in realistic environments, because needs to enumerate all states.
Approximation by exploring parts of search tree, random or heuristics.
DYNA: model-free incrementally updated through samples from world model
MB-ness forms a continuous dimension that varies in informational richness, so I wasn't that naive :)
the inflexibility of habitual control trades off with gains in speed and consistency of action
OMMMGGGGG dopamine signals MB not MF, and therefore there may not be MF in the brain at all !!!
},
file = {Miller_et_al_2018_Realigning_Models_of_Habitual_and_Goal-Directed_Decision-Making.pdf:files/6317/Miller_et_al_2018_Realigning_Models_of_Habitual_and_Goal-Directed_Decision-Making.pdf:application/pdf;ScienceDirect Snapshot:files/5788/B9780128120989000188.html:text/html},
}
@article{gershman_retrospective_2014,
title = {Retrospective revaluation in sequential decision making: {A} tale of two systems.},
volume = {143},
issn = {1939-2222, 0096-3445},
shorttitle = {Retrospective revaluation in sequential decision making},
url = {http://doi.apa.org/getdoi.cfm?doi=10.1037/a0030844},
doi = {10.1037/a0030844},
abstract = {Recent computational theories of decision making in humans and animals have portrayed 2 systems locked in a battle for control of behavior. One system—variously termed model-free or habitual—favors actions that have previously led to reward, whereas a second— called the model-based or goal-directed system—favors actions that causally lead to reward according to the agent’s internal model of the environment. Some evidence suggests that control can be shifted between these systems using neural or behavioral manipulations, but other evidence suggests that the systems are more intertwined than a competitive account would imply. In 4 behavioral experiments, using a retrospective revaluation design and a cognitive load manipulation, we show that human decisions are more consistent with a cooperative architecture in which the model-free system controls behavior, whereas the model-based system trains the model-free system by replaying and simulating experience.},
language = {en},
number = {1},
urldate = {2020-11-13},
journal = {Journal of Experimental Psychology: General},
author = {Gershman, Samuel J. and Markman, Arthur B. and Otto, A. Ross},
year = {2014},
pages = {182--194},
file = {Gershman_et_al_2014_Retrospective_revaluation_in_sequential_decision_making.pdf:files/5776/Gershman_et_al_2014_Retrospective_revaluation_in_sequential_decision_making.pdf:application/pdf},
}
@article{crawford_biologically_2016,
title = {Biologically {Plausible}, {Human}-{Scale} {Knowledge} {Representation}},
volume = {40},
issn = {03640213},
url = {http://doi.wiley.com/10.1111/cogs.12261},
doi = {10.1111/cogs.12261},
abstract = {Several approaches to implementing symbol-like representations in neurally plausible models have been proposed. These approaches include binding through synchrony (Shastri \& Ajjanagadde, 1993), “mesh” binding (van der Velde \& de Kamps, 2006), and conjunctive binding (Smolensky, 1990). Recent theoretical work has suggested that most of these methods will not scale well, that is, that they cannot encode structured representations using any of the tens of thousands of terms in the adult lexicon without making implausible resource assumptions. Here, we empirically demonstrate that the biologically plausible structured representations employed in the Semantic Pointer Architecture (SPA) approach to modeling cognition (Eliasmith, 2013) do scale appropriately. Specifically, we construct a spiking neural network of about 2.5 million neurons that employs semantic pointers to successfully encode and decode the main lexical relations in WordNet, which has over 100,000 terms. In addition, we show that the same representations can be employed to construct recursively structured sentences consisting of arbitrary WordNet concepts, while preserving the original lexical structure. We argue that these results suggest that semantic pointers are uniquely well-suited to providing a biologically plausible account of the structured representations that underwrite human cognition.},
language = {en},
number = {4},
urldate = {2020-11-17},
journal = {Cognitive Science},
author = {Crawford, Eric and Gingerich, Matthew and Eliasmith, Chris},
month = may,
year = {2016},
pages = {782--821},
annote = {Extracted Annotations (3/7/2021, 3:58:10 PM)
"The extra terms in Eq. (2) can be treated as noise because a, c, d, e and f are randomly chosen vectors." (Crawford, et and al 2016:790)
"The inverses of these relations are also implicitly included, although we do not test their extraction as this requires more complex control of signal flow that is beyond our present scope." (Crawford, et and al 2016:791)
"We then assign each WordNet synset a Ddimensional vector called an ID-vector, chosen uniformly at random from the Ddimensional unit hypersphere, which acts as a unique identifier for that synset" (Crawford, et and al 2016:792)
"in human knowledge bases, concepts with multiple relations of exactly the same type may be rare or non-existent" (Crawford, et and al 2016:795)
Q: query vector (dimension D) (note on p.805)
"role vectors are chosen randomly from the set of so-called "unitary" vectors instead of from the unit hypersphere as with relation-type vectors" (Crawford, et and al 2016:809)
"involution is their exact inverse" (Crawford, et and al 2016:809)},
file = {Crawford_et_al_2016_Biologically_Plausible,_Human-Scale_Knowledge_Representation.pdf:files/5852/Crawford_et_al_2016_Biologically_Plausible,_Human-Scale_Knowledge_Representation.pdf:application/pdf},
}
@article{kaptelinin_activity_1996,
title = {Activity {Theory}: {Implications} for {Human}-{Computer} {Interaction}},
doi = {10.1007/978-3-642-85104-9_2},
language = {en},
journal = {Context and consciousness: Activity theory and human-computer interaction},
author = {Kaptelinin, Victor},
year = {1996},
pages = {102--116},
annote = {Extracted Annotations (3/7/2021, 3:58:31 PM)
"Like Piaget's (1950)" (Kaptelinin 1996:103)
"Gibson's (1979)" (Kaptelinin 1996:103)
"Bødker 1991" (Kaptelinin 1996:103)
"1978," (Kaptelinin 1996:103)
"Leont'ev" (Kaptelinin 1996:103)
"activity" (Kaptelinin 1996:103)
"human interaction with the objective reality" (Kaptelinin 1996:104)
"So human beings live in an environment that is meaningful in itself" (Kaptelinin 1996:104)
"This environment consists of entities that combine all kinds of objective features," (Kaptelinin 1996:104)
"including the culturally determined ones, which, in turn, determine the way people act on these entities." (Kaptelinin 1996:104)
"The third basic principle of activity theory is the hierarchical structure of activity" (Kaptelinin 1996:104)
"objects to which these processes are oriented." (Kaptelinin 1996:104)
"operation," (Kaptelinin 1996:104)
"But" (Kaptelinin 1996:104)
need for complex activity recognition? (note on p.104)
"taking into consideration the" (Kaptelinin 1996:104)
"Activities are oriented to motives," (Kaptelinin 1996:104)
Motiv (note on p.104)
"Actions are the processes functionally subordinated to activities;" (Kaptelinin 1996:104)
"a real-life situation, it is often necessary to predict human behavior" (Kaptelinin 1996:104)
necessity of activity prediction (note on p.104)
"differentiate among motive" (Kaptelinin 1996:104)
"conscious goals." (Kaptelinin 1996:104)
"Actions are realized through operations" (Kaptelinin 1996:104)
"The fourth principle of activity theory, that of internalization-externalization" (Kaptelinin 1996:104)
"The fifth principle is mediation. Human" (Kaptelinin 1996:104)
"In" (Kaptelinin 1996:104)
"These tools specify their modes of" (Kaptelinin 1996:104)
"As Kuutti (1992) argued, activity provides a ''minimal meaningful context'" (Kaptelinin 1996:105)
"customizing the system according to their current needs (Henderson and Kyng 1991)." (Kaptelinin 1996:105)
"A possible way to cope with unpredictable structural changes in a user's activity is to support users in customizing the system according to their current needs (Henderson and Kyng 1991). Yet this is not a" (Kaptelinin 1996:105)},
file = {Kaptelinin_1996_Activity_Theory.pdf:files/5813/Kaptelinin_1996_Activity_Theory.pdf:application/pdf},
}
@article{engestrom_activity_2000,
title = {Activity theory as a framework for analyzing and redesigning work},
volume = {43},
issn = {0014-0139, 1366-5847},
url = {https://doi.org/10.1080/001401300409143},
doi = {10.1080/001401300409143},
abstract = {Cultural-historical activity theory is a new framework aimed at transcending the dichotomies of micro- and macro-, mental and material, observation and intervention in analysis and redesign of work. The approach distinguishes between short-lived goal-directed actions and durable, object-oriented activity systems. A historically evolving collective activity system, seen in its network relations to other activity systems, is taken as the prime unit of analysis against which scripted strings of goal-directed actions and automatic operations are interpreted. Activity systems are driven by communal motives that are often difficult to articulate for individual participants. Activity systems are in constant movement and internally contradictory. Their systemic contradictions, manifested in disturbances and mundane innovations, offer possibilities for expansive developmental transformations. Such transformations proceed through stepwise cycles of expansive learning which begin with actions of questioning the existing standard practice, then proceed to actions of analyzing its contradictions and modelling a vision for its zone of proximal development, then to actions of examining and implementing the new model in practice. New forms of work organization increasingly require negotiated ‘knotworking’ across boundaries. Correspondingly, expansive learning increasingly involves horizontal widening of collective expertise by means of debating, negotiating and hybridizing different perspectives and conceptualizations. Findings from a longitudinal intervention study of children's medical care illuminate the theoretical arguments.},
language = {eng},
number = {7},
urldate = {2020-11-16},
journal = {Ergonomics},
author = {Engestrom, Yrjo},
month = jul,
year = {2000},
pmid = {10929830},
keywords = {Humans, Finland, Activity theory, Adult, Child, Critical Pathways, Hospitals, Pediatric, Man-Machine Systems, Outpatient Clinics, Hospital, Task Performance and Analysis, User-Computer Interface, Expansive Learning},
pages = {960--974},
file = {Engestrom_2000_Activity_theory_as_a_framework_for_analyzing_and_redesigning_work.pdf:files/5814/Engestrom_2000_Activity_theory_as_a_framework_for_analyzing_and_redesigning_work.pdf:application/pdf},
}
@article{albero_interet_2014,
title = {L'intérêt pour l'activité en sciences de l'éducation. {Vers} une épistémologie fédératrice ?},
volume = {11},
shorttitle = {L'intérêt pour l'activité en sciences de l'éducation. {Vers} une épistémologie fédératrice ?},
url = {https://hal.archives-ouvertes.fr/hal-01712411},
abstract = {Depuis une dizaine d’années, les travaux centrés sur la notion d’activité se sont multipliés. Cette contribution propose de faire un bilan des orientations principales qui les structurent en sciences de l’éducation. Au-delà de leur description, l’analyse de leurs convergences permet de dégager des pistes fédératrices potentiellement utiles pour une pluridiscipline qui, comme d’autres (économie, gestion et management, information et communication, santé, sports, travail social) porte sur une grande diversité de champs de pratiques.},
urldate = {2020-11-16},
journal = {TransFormations : Recherches en éducation et formation des adultes},
author = {Albero, Brigitte and Guérin, Jérôme},
year = {2014},
note = {Publisher: Institut CUEEP, Lille 1},
keywords = {Activity theory, Epistémologie, Formation d'adultes, Sciences de l'éducation},
pages = {11--45},
file = {Albero_Guerin_2014_L'interet_pour_l'activite_en_sciences_de_l'education.pdf:files/5796/Albero_Guerin_2014_L'interet_pour_l'activite_en_sciences_de_l'education.pdf:application/pdf},
}
@article{romero_elearn_2016,
title = {elearn {Magazine}: {The} {Move} is {On}! {From} the {Passive} {Multimedia} {Learner} to the {Engaged} {Co}-creator},
shorttitle = {elearn {Magazine}},
url = {https://elearnmag.acm.org/archive.cfm?aid=2893358},
abstract = {The educational integration of information and communication technologies (ICTs) has led to unfounded hopes of meeting many recurring educational challenges: from increasing learner motivation to lowering drop-out rates. ICTs are not an educational revolution per se; in some situations, their pedagogical usage lead to truly technologically-enhanced learning (TEL) situations, whereas in others, ICTs could relegate the learner to a passive spectator or low-interactivity user/consumer of multimedia content that limits the implementation of a socio-constructivist learning process based on a collaborative knowledge construction process. In this article, we analyze the limits of techno-centric approaches in the integration process of ICTs to teaching and learning, and argue for active learning and reflexive approaches to TEL.},
urldate = {2020-11-16},
journal = {eLearn Magazine, an ACM Publication},
author = {Romero, Margarida and Laferrière, Thérèse and Power, Thomas Michael},
month = mar,
year = {2016},
file = {Snapshot:files/5806/archive.html:text/html},
}
@book{polya_how_1945,
edition = {Princeton University Press},
series = {Princeton {Science} {Library}},
title = {How to {Solve} {It}: {A} {New} {Aspect} of {Mathematical} {Method}},
isbn = {0-691-11966-X},
shorttitle = {How to {Solve} {It}},
url = {https://b-ok.cc/book/2216490/258273},
urldate = {2020-11-16},
author = {Polya, George},
year = {1945},
file = {How to Solve It A New Aspect of Mathematical Method by G. Polya.epub:files/5799/How to Solve It A New Aspect of Mathematical Method by G. Polya (z-lib.org).epub:application/epub+zip},
}
@article{march_exploration_1991,
title = {Exploration and {Exploitation} in {Organizational} {Learning}},
volume = {2},
issn = {1047-7039},
url = {https://www.jstor.org/stable/2634940},
doi = {10.1287/orsc.2.1.71},
abstract = {This paper considers the relation between the exploration of new possibilities and the exploitation of old certainties in organizational learning. It examines some complications in allocating resources between the two, particularly those introduced by the distribution of costs and benefits across time and space, and the effects of ecological interaction. Two general situations involving the development and use of knowledge in organizations are modeled. The first is the case of mutual learning between members of an organization and an organizational code. The second is the case of learning and competitive advantage in competition for primacy. The paper develops an argument that adaptive processes, by refining exploitation more rapidly than exploration, are likely to become effective in the short run but self-destructive in the long run. The possibility that certain common organizational practices ameliorate that tendency is assessed.},
language = {en},
number = {1},
urldate = {2020-11-16},
journal = {Organization Science},
author = {March, James G.},
year = {1991},
note = {Publisher: INFORMS},
pages = {71--87},
file = {March_1991_Exploration_and_Exploitation_in_Organizational_Learning.pdf:files/5801/March_1991_Exploration_and_Exploitation_in_Organizational_Learning.pdf:application/pdf},
}
@inproceedings{romero_creacube_2017,
title = {{CreaCube}, analyse de la résolution créative de problèmes par le biais d’une tâche de robotique modulaire},
language = {fr},
booktitle = {Journées {Nationales} de la {Recherche} en {Robotique}, {JNRR} 2017},
publisher = {Femto-st},
author = {Romero, Margarida},
year = {2017},
pages = {1},
file = {Romero_2017_CreaCube,_analyse_de_la_resolution_creative_de_problemes_par_le_biais_d’une.pdf:files/5811/Romero_2017_CreaCube,_analyse_de_la_resolution_creative_de_problemes_par_le_biais_d’une.pdf:application/pdf},
}
@misc{lhuiller_interpretabilite_2020,
title = {Interprétabilité vs explicabilité : l’interprétabilité selon différentes approches (2/3)},
url = {http://www.scilogs.fr/intelligence-mecanique/interpretabilite-vs-explicabilite-linterpretabilite-selon-differentes-approches-2-3/},
urldate = {2020-11-16},
journal = {Blog Binaire, LeMonde.fr},
author = {Lhuiller, Marine and Chraibi Kaadoud, Ikram},
month = oct,
year = {2020},
}
@misc{lhuiller_interpretabilite_2020-1,
title = {Interprétabilité vs explicabilité : comprendre vs expliquer son réseau de neurones (1/3)},
url = {http://www.scilogs.fr/intelligence-mecanique/interpretabilite-vs-explicabilite-comprendre-vs-expliquer-son-reseau-de-neurone-1-3/},
urldate = {2020-11-16},
journal = {Blog Binaire, LeMonde.fr},
author = {Lhuiller, Marine and Chraibi Kaadoud, Ikram},
month = sep,
year = {2020},
}
@article{connolly_nonholonomic_1994,
title = {Nonholonomic {Path} {Planning} {Using} {Harmonic} {Functions}},
abstract = {A method is presented for planning obstacle-avoiding paths for a system which exhibits nonholonomic constraints. The method is based on the use of harmonic functions. Linear constraints on the velocity of a nonholonomic system can be directly expressed as Neumann boundary conditions for a harmonic function. Such boundary conditions are easily represented in a resistive network. The resulting potential represents an integration of nonholonomic constraints over an admissible subset of configuration space. The method is applied to path planning for simple wheeled vehicles. 1 Introduction This paper draws on the relationship between harmonic functions and resistive networks to propose a new method for planning the motion of nonholonomic systems. Simple nonholonomic constraints [1] restrict the velocity of mechanical systems to a linear subspace of their configuration space. These constraints bear a resemblance to the Neumann boundary condition for harmonic functions. Although nonho...},
language = {en},
author = {Connolly, Christopher and Grupen, Roderic},
month = sep,
year = {1994},
pages = {21},
file = {Connolly_Grupen_1994_Nonholonomic_Path_Planning_Using_Harmonic_Functions.pdf:files/5791/Connolly_Grupen_1994_Nonholonomic_Path_Planning_Using_Harmonic_Functions.pdf:application/pdf},
}
@article{poortvliet_achievement_2007,
title = {Achievement {Goals} and {Interpersonal} {Behavior}: {How} {Mastery} and {Performance} {Goals} {Shape} {Information} {Exchange}},
volume = {33},
issn = {0146-1672, 1552-7433},
shorttitle = {Achievement {Goals} and {Interpersonal} {Behavior}},
url = {https://journals.sagepub.com/doi/10.1177/0146167207305536},
doi = {10.1177/0146167207305536},
abstract = {The present research examines the impact of achievement goals on task-related information exchange. Studies 1 and 2 reveal that relative to those with mastery g...},
language = {en},
number = {10},
urldate = {2020-11-16},
journal = {Personality and Social Psychology Bulletin},
author = {Poortvliet, P. Marijn and Janssen, Onne and Yperen, Nico W. Van and Vliert, Evert Van de},
month = oct,
year = {2007},
note = {Publisher: Sage PublicationsSage CA: Los Angeles, CA},
pages = {1435--1447},
file = {Poortvliet_et_al_2007_Achievement_Goals_and_Interpersonal_Behavior.pdf:files/5816/Poortvliet_et_al_2007_Achievement_Goals_and_Interpersonal_Behavior.pdf:application/pdf},
}
@article{leblanc_exploiter_2020,
title = {Exploiter les corpus vidéo à des fins de recherche : innovations méthodologiques et effets sur les pratiques en sciences de l’éducation},
copyright = {La revue Éducation et socialisation est mise à disposition selon les termes de la Licence Creative Commons Attribution - Pas d'Utilisation Commerciale - Pas de Modification 4.0 International.},
issn = {0992-3705},
shorttitle = {Exploiter les corpus vidéo à des fins de recherche},
url = {http://journals.openedition.org/edso/9034},
doi = {10.4000/edso.9034},
abstract = {La technologie vidéo a connu un développement rapide depuis une dizaine d’années et offre un potentiel riche pour les chercheurs en sciences de l’éducation. Le but de cet article est d’étudier les liens entre des innovations portant sur les usages de corpus vidéo dans les recherches en sciences de l’éducation qui ont émergé à un moment donné dans le paysage scientifique français et les changements dans les pratiques des chercheurs qu’elles ont ou non induits, suscités, favorisés. Sur la base d’une note de synthèse, trois innovations jugées particulièrement significatives pour la recherche ont tout d’abord été choisies. Les ressources documentaires et expérientielles les plus pertinentes au regard de ces innovations ont ensuite été recherchées et regroupées. Elles ont enfin été resituées dans leur contexte scientifique, historique, social et technologique spécifique puis analysées afin de comprendre les changements qu’elles ont ou non accompagnés et sur quelle temporalité.},
language = {fr},
number = {55},
urldate = {2020-11-16},
journal = {Éducation et socialisation. Les Cahiers du CERFEE},
author = {Leblanc, Serge and Gaudin, Cyrille},
month = mar,
year = {2020},
note = {Number: 55
Publisher: Presses universitaires de la méditerranée},
file = {Leblanc_Gaudin_2020_Exploiter_les_corpus_video_a_des_fins_de_recherche.pdf:files/5802/Leblanc_Gaudin_2020_Exploiter_les_corpus_video_a_des_fins_de_recherche.pdf:application/pdf;Snapshot:files/5803/9034.html:text/html},
}
@misc{lhuiller_interpretabilite_2020-2,
title = {Interprétabilité, biais, éthique et transparence : quelles relations ? (3/3)},
url = {http://www.scilogs.fr/intelligence-mecanique/interpretabilite-biais-ethique-et-transparence-quelles-relations-3-3/},
urldate = {2020-11-16},
journal = {Blog Binaire, LeMonde.fr},
author = {Lhuiller, Marine and Chraibi Kaadoud, Ikram},
month = oct,
year = {2020},
}
@book{dowek_langues_2019,
edition = {Le Pommier},
title = {Langues et langages : {Ce} dont on ne peut parler, il faut l'écrire},
isbn = {978-2-7465-1800-1},
url = {https://www.editions-lepommier.fr/ce-dont-ne-peut-parler-il-faut-lecrire},
language = {fr},
urldate = {2020-11-16},
author = {Dowek, Gilles},
month = sep,
year = {2019},
}
@phdthesis{curran_exploration_2008,
title = {Exploration and exploitation: {A} new explanation of differential goal-setting effects},
shorttitle = {Exploration and exploitation},
url = {https://search.proquest.com/openview/c616a4f6dd3ff1835b2450da541d68fa/1?pq-origsite=gscholar&cbl=18750&diss=y},
language = {en},
urldate = {2020-11-16},
school = {Michigan State University},
author = {Curran, Paul G},
year = {2008},
annote = {Ce PDF n'est qu'un aperçu car je n'ai pas accès au fichier complet (peut-être que tu l'as Margarida ?)},
file = {Curran_2008_Exploration_and_exploitation.pdf:files/5800/Curran_2008_Exploration_and_exploitation.pdf:application/pdf},
}
@article{chi_active-constructive-interactive_2009,
title = {Active-{Constructive}-{Interactive}: {A} {Conceptual} {Framework} for {Differentiating} {Learning} {Activities}},
volume = {1},
issn = {17568757, 17568765},
shorttitle = {Active-{Constructive}-{Interactive}},
url = {http://doi.wiley.com/10.1111/j.1756-8765.2008.01005.x},
doi = {10.1111/j.1756-8765.2008.01005.x},
abstract = {Active, constructive, and interactive are terms that are commonly used in the cognitive and learning sciences. They describe activities that can be undertaken by learners. However, the literature is actually not explicit about how these terms can be defined; whether they are distinct; and whether they refer to overt manifestations, learning processes, or learning outcomes. Thus, a framework is provided here that offers a way to differentiate active, constructive, and interactive in terms of observable overt activities and underlying learning processes. The framework generates a testable hypothesis for learning: that interactive activities are most likely to be better than constructive activities, which in turn might be better than active activities, which are better than being passive. Studies from the literature are cited to provide evidence in support of this hypothesis. Moreover, postulating underlying learning processes allows us to interpret evidence in the literature more accurately. Specifying distinct overt activities for active, constructive, and interactive also offers suggestions for how learning activities can be coded and how each kind of activity might be elicited.},
language = {en},
number = {1},
urldate = {2020-11-16},
journal = {Topics in Cognitive Science},
author = {Chi, Michelene T. H.},
month = jan,
year = {2009},
pages = {73--105},
annote = {Extracted Annotations (3/7/2021, 3:57:35 PM)
"steering" (Chi 2009:76)
"peddling" (Chi 2009:76)
"looking at and searching" (Chi 2009:76)
"pointing to or gesturing" (Chi 2009:76)
"underlining or copying-and-pasting" (Chi 2009:76)
"repeating sentences" (Chi 2009:76)
"summarizing paragraphs" (Chi 2009:76)
"manipulating" (Chi 2009:76)
"rotating objects" (Chi 2009:76)
"Engaging Activities" (Chi 2009:77)
"Explain or elaborate Justify or provide reasons Connect or link Construct a concept map Reflect, or self-monitor Plan and predict outcomes Generate hypotheses" (Chi 2009:77)
"Self-construction Activities Guided-construction Look, gaze, or fixate Explain or elaborate Activities in Instructional Underline or highlight Justify or provide reasons Dialogue: Gesture or point Connect or link Respond to scafffoldings Paraphrase Construct a concept map Revise errors from fdbk Manipulate objects or tapes Reflect, or self-monitor Sequential or Co-construction Select Plan and predict outcomes Activities in Joint Dialogue: Repeat Generate hypotheses Build on partner's contr Argue, defend Confront or challenge" (Chi 2009:77)},
file = {Chi_2009_Active-Constructive-Interactive.pdf:files/5815/Chi_2009_Active-Constructive-Interactive.pdf:application/pdf},
}
@article{busscher_learning_2019,
title = {Learning in the face of change: {The} {Dutch} {National} {Collaboration} {Programme} on {Air} {Quality}:},
volume = {37(5)},
copyright = {© The Author(s) 2018},
shorttitle = {Learning in the face of change},
url = {https://journals.sagepub.com/doi/10.1177/0263774X18804227},
doi = {10.1177/0263774X18804227},
abstract = {Learning is essential in allowing policies and programmes to become adaptive to uncertain and changing circumstances. In this article, we use the case of the Dutch National Collaboration Programme ...},
language = {en},
urldate = {2020-11-16},
journal = {Environment and Planning C: Politics and Space},
author = {Busscher, Tim and Zuidema, Christian and Tillema, Taede and Arts, Jos},
year = {2019},
note = {Publisher: SAGE PublicationsSage UK: London, England},
pages = {929--945},
file = {Busscher_et_al_2019_Learning_in_the_face_of_change.pdf:files/5794/Busscher_et_al_2019_Learning_in_the_face_of_change.pdf:application/pdf},
}
@article{brand-gruwel_information_2005,
title = {Information problem solving by experts and novices: analysis of a complex cognitive skill},
volume = {21},
issn = {07475632},
shorttitle = {Information problem solving by experts and novices},
url = {https://linkinghub.elsevier.com/retrieve/pii/S0747563204001591},
doi = {10.1016/j.chb.2004.10.005},
abstract = {In (higher) education students are often faced with information problems: tasks or assignments that require them to identify information needs, locate corresponding information sources, extract and organize relevant information from each source, and synthesize information from a variety of sources. It is often assumed that students master this complex cognitive skill of information problem solving all by themselves. In our point of view, however, explicit and intensive instruction is necessary. A skill decomposition is needed in order to design instruction that fosters the development of information problem solving. This research analyzes the information problem solving process of novices and experts in order to reach a detailed skill decomposition. Results reveal that experts spend more time on the main skill Ôdefine problemÕ and more often activate their prior knowledge, elaborate on the content, and regulate their process. Furthermore, experts and novices show little differences in the way they search the Internet. These findings formed the basis for formulating instructional guidelines. Ó 2004 Elsevier Ltd. All rights reserved.},
language = {en},
number = {3},
urldate = {2020-11-16},
journal = {Computers in Human Behavior},
author = {Brand-Gruwel, Saskia and Wopereis, Iwan and Vermetten, Yvonne},
month = may,
year = {2005},
pages = {487--508},
file = {Brand-Gruwel_et_al_2005_Information_problem_solving_by_experts_and_novices.pdf:files/5798/Brand-Gruwel_et_al_2005_Information_problem_solving_by_experts_and_novices.pdf:application/pdf},
}
@article{belkaid_emotional_2017,
title = {Emotional metacontrol of attention: {Top}-down modulation of sensorimotor processes in a robotic visual search task},
volume = {12},
issn = {1932-6203},
shorttitle = {Emotional metacontrol of attention},
url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0184960},
doi = {10.1371/journal.pone.0184960},
abstract = {Emotions play a significant role in internal regulatory processes. In this paper, we advocate four key ideas. First, novelty detection can be grounded in the sensorimotor experience and allow higher order appraisal. Second, cognitive processes, such as those involved in self-assessment, influence emotional states by eliciting affects like boredom and frustration. Third, emotional processes such as those triggered by self-assessment influence attentional processes. Last, close emotion-cognition interactions implement an efficient feedback loop for the purpose of top-down behavior regulation. The latter is what we call ‘Emotional Metacontrol’. We introduce a model based on artificial neural networks. This architecture is used to control a robotic system in a visual search task. The emotional metacontrol intervenes to bias the robot visual attention during active object recognition. Through a behavioral and statistical analysis, we show that this mechanism increases the robot performance and fosters the exploratory behavior to avoid deadlocks.},
language = {en},
number = {9},
urldate = {2020-11-16},
journal = {PLOS ONE},
author = {Belkaid, Marwen and Cuperlier, Nicolas and Gaussier, Philippe},
month = sep,
year = {2017},
note = {Publisher: Public Library of Science},
keywords = {Learning, Robots, Attention, Cognition, Emotions, Sensory perception, Vision, Visual object recognition},
pages = {e0184960},
file = {Belkaid_et_al_2017_Emotional_metacontrol_of_attention.pdf:files/5805/Belkaid_et_al_2017_Emotional_metacontrol_of_attention.pdf:application/pdf},
}
@inproceedings{komer_neural_2019,
address = {Montreal, Canada},
title = {A neural representation of continuous space using fractional binding},
url = {http://compneuro.uwaterloo.ca/publications/komer2019.html},
abstract = {We present a novel method for constructing neurally implemented spatial representations that we show to be useful for building models of spatial cognition. This method represents continuous (i.e., real-valued) spaces using neurons, and identifies a set of operations for manipulating these representations. Specifically, we use “fractional binding” to construct “spatial semantic pointers” (SSPs) that we use to generate and manipulate representations of spatial maps encoding the positions of objects. We show how these representations can be transformed to answer queries about the location and identities of objects, move the relative or global position of items, and answer queries about regions of space, among other things. We demonstrate that the neural implementation in spiking networks of SSPs have similar accuracy and capacity as the mathematical ideal.},
language = {en},
booktitle = {41st {Annual} {Meeting} of the {Cognitive} {Science} {Society}},
publisher = {Cognitive Science Society},
author = {Komer, Brent and Stewart, Terrence C and Voelker, Aaron R and Eliasmith, Chris},
year = {2019},
pages = {6},
file = {Komer_et_al_2019_A_neural_representation_of_continuous_space_using_fractional_binding.pdf:files/5843/Komer_et_al_2019_A_neural_representation_of_continuous_space_using_fractional_binding.pdf:application/pdf},
}
@article{voelker_short_2020,
title = {A short letter on the dot product between rotated {Fourier} transforms},
url = {http://arxiv.org/abs/2007.13462},
abstract = {Spatial Semantic Pointers (SSPs) have recently emerged as a powerful tool for representing and transforming continuous space, with numerous applications to cognitive modelling and deep learning. Fundamental to SSPs is the notion of "similarity" between vectors representing different points in \$n\$-dimensional space -- typically the dot product or cosine similarity between vectors with rotated unit-length complex coefficients in the Fourier domain. The similarity measure has previously been conjectured to be a Gaussian function of Euclidean distance. Contrary to this conjecture, we derive a simple trigonometric formula relating spatial displacement to similarity, and prove that, in the case where the Fourier coefficients are uniform i.i.d., the expected similarity is a product of normalized sinc functions: \${\textbackslash}prod\_\{k=1\}{\textasciicircum}\{n\} {\textbackslash}operatorname\{sinc\} {\textbackslash}left( a\_k {\textbackslash}right)\$, where \${\textbackslash}mathbf\{a\} {\textbackslash}in {\textbackslash}mathbb\{R\}{\textasciicircum}n\$ is the spatial displacement between the two \$n\$-dimensional points. This establishes a direct link between space and the similarity of SSPs, which in turn helps bolster a useful mathematical framework for architecting neural networks that manipulate spatial structures.},
language = {en},
urldate = {2020-11-26},
journal = {arXiv:2007.13462 [cs, q-bio]},
author = {Voelker, Aaron R.},
month = jul,
year = {2020},
note = {arXiv: 2007.13462},
keywords = {Quantitative Biology - Neurons and Cognition, Machine Learning},
annote = {Comment: 4 pages, 3 figures},
file = {Voelker_2020_A_short_letter_on_the_dot_product_between_rotated_Fourier_transforms.pdf:files/5824/Voelker_2020_A_short_letter_on_the_dot_product_between_rotated_Fourier_transforms.pdf:application/pdf},
}
@article{stewart_symbolic_2010,
title = {Symbolic {Reasoning} in {Spiking} {Neurons}: {A} {Model} of the {Cortex}/{Basal} {Ganglia}/{Thalamus} {Loop}},
abstract = {We present a model of symbol manipulation implemented using spiking neurons and closely tied to the anatomy of the cortex, basal ganglia, and thalamus. The model is a generalpurpose neural controller which plays a role analogous to a production system. Information stored in cortex is used by the basal ganglia as the basis for selecting between a set of inferences. When an inference rule is selected, it commands the thalamus to modify and transmit information between areas of the cortex. The system supports special-case and general-purpose inferences, including the ability to remember complex statements and answer questions about them. The resulting model suggests modifications to the standard structure of production system rules, and offers a neurological explanation for the 50 millisecond cognitive cycle time.},
language = {en},
author = {Stewart, Terrence C and Choo, Xuan and Eliasmith, Chris},
year = {2010},
pages = {7},
file = {Stewart_et_al_2010_Symbolic_Reasoning_in_Spiking_Neurons.pdf:files/5825/Stewart_et_al_2010_Symbolic_Reasoning_in_Spiking_Neurons.pdf:application/pdf},
}
@article{wiley_expertise_1998,
title = {Expertise as mental set: {The} effects of domain knowledge in creative problem solving},
volume = {26},
issn = {0090-502X, 1532-5946},
shorttitle = {Expertise as mental set},
url = {http://link.springer.com/10.3758/BF03211392},
doi = {10.3758/BF03211392},
language = {en},
number = {4},
urldate = {2020-11-17},
journal = {Memory \& Cognition},
author = {Wiley, Jennifer},
month = jul,
year = {1998},
note = {Number: 4},
pages = {716--730},
file = {Wiley_1998_Expertise_as_mental_set.pdf:files/5804/Wiley_1998_Expertise_as_mental_set.pdf:application/pdf},
}
@article{zelazo_early_1997,
title = {Early {Development} of {Executive} {Function}: {A} {Problem}-{Solving} {Framework}},
volume = {1},
issn = {1089-2680, 1939-1552},
shorttitle = {Early {Development} of {Executive} {Function}},
url = {http://journals.sagepub.com/doi/10.1037/1089-2680.1.2.198},
doi = {10.1037/1089-2680.1.2.198},
abstract = {Executive function (EF) accounts have now been offered for several disorders with childhood onset (e.g., attention-deficit/hyperactivity disorder, autism, early-treated phenylketonuria), and EF has been linked to the development of numerous abilities (e.g., attention, rule use, theory of mind). However, efforts to explain behavior in terms of EF have been hampered by an inadequate characterization of EF itself. What is the function that is accomplished by EF? The present analysis attempts to ground the construct of EF in an account of problem solving and thereby to integrate temporally and functionally distinct aspects of EF within a coherent framework. According to this problem-solving framework, EF is a macroconstruct that spans 4 phases of problem solving (representation, planning, execution, and evaluation). When analyzed into subfunctions, macroconstructs such as EF permit the integration of findings from disparate content domains, which are often studied in isolation from the broader context of reasoning and action. A review of the literature on the early development of EF reveals converging evidence for domain-general changes in all aspects of EF.},
language = {en},
number = {2},
urldate = {2020-11-17},
journal = {Review of General Psychology},
author = {Zelazo, Philip David and Carter, Alice and Reznick, J. Steven and Frye, Douglas},
month = jun,
year = {1997},
pages = {198--226},
file = {Zelazo_et_al_1997_Early_Development_of_Executive_Function.pdf:files/5807/Zelazo_et_al_1997_Early_Development_of_Executive_Function.pdf:application/pdf},
}
@article{sannino_double_2015,
series = {The emergence of transformative agency and double stimulation: {Activity}-based studies in the {Vygotskian} tradition},
title = {Double stimulation in the waiting experiment: {Testing} a {Vygotskian} model of the emergence of volitional action},
volume = {4},
issn = {2210-6561},
shorttitle = {Double stimulation in the waiting experiment},
url = {http://www.sciencedirect.com/science/article/pii/S2210656114000634},
doi = {10.1016/j.lcsi.2014.07.002},
abstract = {Vygotsky refers to a waiting experiment and uses it as an example to conceptualize double stimulation as human beings' ability to willfully transform conflictual circumstances with the help of auxiliary means. This experiment can be considered a key to a Vygotskian view on this topic, which can significantly contribute to today's discussions of ways to support transformative agency. In this article we provide an overview of a waiting experiment, recently conducted with the specific aim of testing a Vygotskian model of the emergence of volitional action. While confirming this model, the findings suggest two extensions to it. One extension is the inclusion of participants' life activity. The second extension, closely related to the first one, points at fluid and iterative movements that may occur between and within the phases of the model, due to the interference of life activity and conformity to the experimental setup.},
language = {en},
urldate = {2020-11-17},
journal = {Learning, Culture and Social Interaction},
author = {Sannino, Annalisa and Laitinen, Anne},
month = mar,
year = {2015},
keywords = {Conflict of motives, Double stimulation, Volitional action, Waiting experiment},
pages = {4--18},
file = {Sannino_Laitinen_2015_Double_stimulation_in_the_waiting_experiment.pdf:files/5809/Sannino_Laitinen_2015_Double_stimulation_in_the_waiting_experiment.pdf:application/pdf;ScienceDirect Snapshot:files/5808/S2210656114000634.html:text/html},
}
@article{sannino_cultural-historical_2018,
title = {Cultural-historical activity theory: founding insights and new challenges},
volume = {14},
issn = {1816-5435, 2224-8935},
shorttitle = {Cultural-historical activity theory},
url = {https://psyjournals.ru/en/kip/2018/n3/Sannino_Engestrom.shtml},
doi = {10.17759/chp.2018140304},
abstract = {The article presents central ideas and future challenges of cultural-historical activity theory, focusing specifically on the work of the so-called Helsinki school of activity theory. We first introduce the revolutionary roots of the theory in the works of Marx and Vygotsky, and the evolution of the unit of analysis through different generations of activity theory. We then discuss the foundational role of historicity and dialectics in activity theory. We identify two central epistemological-methodological principles that guide activity-theoretical studies, namely the principle of double stimulation and the principle of ascending from the abstract to the concrete. These principles lead us to emphasize formative interventions as a powerful way to conduct societally impactful activity-theoretical research. We conclude by pointing out some major challenges facing activity theory in the 21st century.
,
Статья посвящена основным идеям культурно-исторической теории деятельности и вызовам нового времени, встающим перед ней. Особое внимание уделяется работе так называемой Хельсинской школы теории деятельности. В первой части статьи мы описываем революционные идеи, лежащие в основе теории и уходящие корнями в работы Маркса и Выготского, а также рассматриваем, как менялись представления о единице анализа на разных этапах становления теории деятельности. Затем мы переходим к обсуждению основополагающей роли историчности и диалектичности в развитии теории деятельности, описываем два ключевых методологических и эпистемологических принципа деятельностных исследований — принцип двойной стимуляции и принцип восхождения от общего к частному. Опора на эти принципы дает нам возможность утверждать, что формирующие интервенции — мощный инструмент в реализации социально значимых, эффективных деятельностных исследований. В заключительной части статьи мы рассматриваем основные вызовы, с которыми придется столкнуться теории деятельности в XXI веке.},
language = {en},
number = {3},
urldate = {2020-11-17},
journal = {Cultural-Historical Psychology},
author = {Sannino, A. and Engeström, Y.},
year = {2018},
note = {Number: 3},
pages = {43--56},
file = {Sannino_Engestrom_2018_Cultural-historical_activity_theory.pdf:files/5810/Sannino_Engestrom_2018_Cultural-historical_activity_theory.pdf:application/pdf},
}
@inproceedings{rougier_open_2016,
title = {Open {Science}},
url = {https://hal.inria.fr/hal-01418314},
abstract = {L’Open science est un mouvement créé par une communauté de chercheu•r•ses. Né d’un constat, celui des difficultés et des obstacles quotidiens que rencontre la communauté scientifique, l’Open science tente d’apporter des solutions aux failles du système de recherche actuel. Si l’Open science s’inscrit donc dans un contexte bien précis et actuel, il ne s’agit pas, cependant, d’un phénomène nouveau. Les notions de patrimoine, de dissémination du savoir et de communauté scientifique sont anciennes. Toutefois, ce phénomène connaît une résurgence certaine grâce au développement des technologies d’information et de communication (TIC). Le numérique permet en effet de faire émerger de nouvelles possibilités en terme de communication, d’échanges entre les chercheur•es•s et de créer de nouveaux modèles de recherche collective et collaborative inclusifs. Ainsi, quelles sont les différentes formes de l’Open science ? Qui sont ses acteurs? Dans quel contexte ce mouvement est-il apparu ? Dans quelle mesure ce phénomène nous éclaire-t-il sur l’évolution du concept de science ? Dans une perspective historique, le mouvement actuel de l’Open science représente-t-il une rupture ou bien une continuité ?},
language = {en},
urldate = {2020-11-17},
author = {Rougier, Nicolas P.},
month = nov,
year = {2016},
pages = {35},
file = {Rougier_2016_Open_Science.pdf:files/5790/Rougier_2016_Open_Science.pdf:application/pdf},
}
@incollection{denoeux_representations_2020,
address = {Cham},
title = {Representations of {Uncertainty} in {AI}: {Beyond} {Probability} and {Possibility}},
isbn = {978-3-030-06164-7},
shorttitle = {Representations of {Uncertainty} in {AI}},
url = {https://doi.org/10.1007/978-3-030-06164-7_4},
abstract = {This chapter completes the survey of the existing frameworks for representing uncertain and incomplete information, started in the previous chapter of this volume. The theory of belief functions and the theory of imprecise probabilities are presented. The latter setting is mathematically more general than the former, and both include probability theory and quantitative possibility theory as particular cases. Their respective knowledge representation capabilities are highlighted.},
language = {en},
urldate = {2020-11-04},
booktitle = {A {Guided} {Tour} of {Artificial} {Intelligence} {Research}: {Volume} {I}: {Knowledge} {Representation}, {Reasoning} and {Learning}},
publisher = {Springer International Publishing},
author = {Denœux, Thierry and Dubois, Didier and Prade, Henri},
editor = {Marquis, Pierre and Papini, Odile and Prade, Henri},
year = {2020},
doi = {10.1007/978-3-030-06164-7_4},
pages = {119--150},
file = {Denoeux_et_al_2020_Representations_of_Uncertainty_in_AI.pdf:files/5851/Denoeux_et_al_2020_Representations_of_Uncertainty_in_AI.pdf:application/pdf;Snapshot:files/5942/978-3-030-06164-7_4.html:text/html;Submitted Version:files/5943/Denœux et al. - 2020 - Representations of Uncertainty in AI Beyond Proba.pdf:application/pdf},
}
@article{tettamanzi_possibilistic_2017,
title = {Possibilistic testing of {OWL} axioms against {RDF} data},
url = {https://hal.inria.fr/hal-01591001},
doi = {10.1016/j.ijar.2017.08.012},
abstract = {We develop the theory of a possibilistic framework for OWL 2 axiom testing against RDF datasets, as an alternative to statistics-based heuristics. The intuition behind it is to evaluate the credibility of OWL 2 axioms based on the evidence available in the form of a set of facts contained in a chosen RDF dataset. To achieve it, we first define the notions of development, content, support , confirmation and counterexample of an axiom. Then we use these notions to define the possibility and necessity of an axiom and its acceptance/rejection index combining both of them. Finally, we report a practical application of the proposed framework to test SubClassOf axioms against the DBpedia RDF dataset.},
language = {en},
urldate = {2020-11-04},
journal = {International Journal of Approximate Reasoning},
author = {Tettamanzi, Andrea and Zucker, Catherine Faron and Gandon, Fabien},
year = {2017},
file = {Tettamanzi_et_al_2017_Possibilistic_testing_of_OWL_axioms_against_RDF_data.pdf:files/5789/Tettamanzi_et_al_2017_Possibilistic_testing_of_OWL_axioms_against_RDF_data.pdf:application/pdf},
}
@article{scardapane_complex-valued_2018,
title = {Complex-valued {Neural} {Networks} with {Non}-parametric {Activation} {Functions}},
url = {http://arxiv.org/abs/1802.08026},
abstract = {Complex-valued neural networks (CVNNs) are a powerful modeling tool for domains where data can be naturally interpreted in terms of complex numbers. However, several analytical properties of the complex domain (e.g., holomorphicity) make the design of CVNNs a more challenging task than their real counterpart. In this paper, we consider the problem of flexible activation functions (AFs) in the complex domain, i.e., AFs endowed with sufficient degrees of freedom to adapt their shape given the training data. While this problem has received considerable attention in the real case, a very limited literature exists for CVNNs, where most activation functions are generally developed in a split fashion (i.e., by considering the real and imaginary parts of the activation separately) or with simple phase-amplitude techniques. Leveraging over the recently proposed kernel activation functions (KAFs), and related advances in the design of complex-valued kernels, we propose the first fully complex, non-parametric activation function for CVNNs, which is based on a kernel expansion with a fixed dictionary that can be implemented efficiently on vectorized hardware. Several experiments on common use cases, including prediction and channel equalization, validate our proposal when compared to real-valued neural networks and CVNNs with fixed activation functions.},
urldate = {2020-11-04},
journal = {arXiv:1802.08026 [cs]},
author = {Scardapane, Simone and Van Vaerenbergh, Steven and Hussain, Amir and Uncini, Aurelio},
month = feb,
year = {2018},
note = {arXiv: 1802.08026},
keywords = {Computer Science - Neural and Evolutionary Computing},
file = {arXiv.org Snapshot:files/5833/1802.html:text/html;Scardapane_et_al_2018_Complex-valued_Neural_Networks_with_Non-parametric_Activation_Functions.pdf:files/5832/Scardapane_et_al_2018_Complex-valued_Neural_Networks_with_Non-parametric_Activation_Functions.pdf:application/pdf},
}
@incollection{marquis_chapitre_2014,
edition = {Cepuades},
series = {Panorama de l'intelligence artificielle},
title = {Chapitre 3 : {Représentation} de l'incertitude en intelligence artificielle},
volume = {1},
isbn = {978-2-36493-041-4},
url = {https://www.cepadues.com/livres/representation-des-connaissances-formalisation-des-raisonnements-volume-1serie-panorama-intelligence-artificielle-9782364930414.html},
language = {fr},
urldate = {2020-11-17},
booktitle = {Représentation des connaissances et formalisation des raisonnements},
author = {Marquis, Pierre and Papini, Odile and Prade, Henri},
year = {2014},
file = {Marquis_et_al_2014_Chapitre_3.pdf:files/5839/Marquis_et_al_2014_Chapitre_3.pdf:application/pdf},
}
@inproceedings{troffaes_connection_2011,
address = {France},
title = {On the connection between probability boxes and possibility measures},
isbn = {978-90-78677-00-0},
url = {http://www.atlantis-press.com/php/paper-details.php?id=2335},
doi = {10.2991/eusflat.2011.150},
abstract = {We explore the relationship between p-boxes on totally preordered spaces and possibility measures. We start by demonstrating that only those p-boxes who have 0–1valued lower or upper cumulative distribution function can be possibility measures, and we derive expressions for their natural extension in this case. Next, we establish necessary and sufficient conditions for a p-box to be a possibility measure. Finally, we show that almost every possibility measure can be modelled by a p-box. Whence, any techniques for p-boxes can be readily applied to possibility measures. We demonstrate this by deriving joint possibility measures from marginals, under varying assumptions of independence, using a technique known for p-boxes.},
language = {en},
urldate = {2020-11-17},
booktitle = {Proceedings of the 7th conference of the {European} {Society} for {Fuzzy} {Logic} and {Technology} ({EUSFLAT}-2011)},
publisher = {Atlantis Press},
author = {Troffaes, Matthias C. M. and Miranda, Enrique and Destercke, Sebastien},
year = {2011},
keywords = {coherent upper previsions, maxitive measures, natural extension, pboxes, Possibility measures},
file = {Troffaes_et_al_2011_On_the_connection_between_probability_boxes_and_possibility_measures.pdf:files/5768/Troffaes_et_al_2011_On_the_connection_between_probability_boxes_and_possibility_measures.pdf:application/pdf},
}
@incollection{dubois_possibility_2015,
address = {Berlin, Heidelberg},
series = {Springer {Handbooks}},
title = {Possibility {Theory} and {Its} {Applications}: {Where} {Do} {We} {Stand}?},
isbn = {978-3-662-43505-2},
shorttitle = {Possibility {Theory} and {Its} {Applications}},
url = {https://doi.org/10.1007/978-3-662-43505-2_3},
abstract = {This chapter provides an overview of possibility theory, emphasizing its historical roots and its recent developments. Possibility theory lies at the crossroads between fuzzy sets, probability, and nonmonotonic reasoning. Possibility theory can be cast either in an ordinal or in a numerical setting. Qualitative possibility theory is closely related to belief revision theory, and commonsense reasoning with exception-tainted knowledge in artificial intelligence. Possibilistic logic provides a rich representation setting, which enables the handling of lower bounds of possibility theory measures, while remaining close to classical logic. Qualitative possibility theory has been axiomatically justified in a decision-theoretic framework in the style of Savage, thus providing a foundation for qualitative decision theory. Quantitative possibility theory is the simplest framework for statistical reasoning with imprecise probabilities. As such, it has close connections with random set theory and confidence intervals, and can provide a tool for uncertainty propagation with limited statistical or subjective information.},
language = {en},
urldate = {2020-11-05},
booktitle = {Springer {Handbook} of {Computational} {Intelligence}},
publisher = {Springer},
author = {Dubois, Didier and Prade, Henry},
editor = {Kacprzyk, Janusz and Pedrycz, Witold},
year = {2015},
doi = {10.1007/978-3-662-43505-2_3},
keywords = {Formal Concept Analysis, Possibilistic Logic, Possibility Distribution, Possibility Theory, Belief function},
pages = {31--60},
file = {Dubois_Prade_2015_Possibility_Theory_and_Its_Applications.pdf:files/5845/Dubois_Prade_2015_Possibility_Theory_and_Its_Applications.pdf:application/pdf},
}
@incollection{denoeux_representations_2020-1,
address = {Cham},
title = {Representations of {Uncertainty} in {AI}: {Probability} and {Possibility}},
isbn = {978-3-030-06164-7},
shorttitle = {Representations of {Uncertainty} in {Artificial} {Intelligence}},
url = {https://doi.org/10.1007/978-3-030-06164-7_3},
abstract = {Due to its major focus on knowledge representation and reasoning, artificial intelligence was bound to deal with various frameworks for the handling of uncertainty: probability theory, but more recent approaches as well: possibility theory, evidence theory, and imprecise probabilities. The aim of this chapter is to provide an introductive survey that lays bare specific features of two basic frameworks for representing uncertainty: probability theory and possibility theory, while highlighting the main issues that the task of representing uncertainty is faced with. This purpose also provides the opportunity to position related topics, such as rough sets and fuzzy sets, respectively motivated by the need to account for the granularity of representations as induced by the choice of a language, and the gradual nature of natural language predicates. Moreover, this overview includes concise presentations of yet other theoretical representation frameworks such as formal concept analysis, conditional events and ranking functions, and also possibilistic logic, in connection with the uncertainty frameworks addressed here. The next chapter in this volume is devoted to more complex frameworks: belief functions and imprecise probabilities.},
language = {en},
urldate = {2020-11-04},
booktitle = {A {Guided} {Tour} of {Artificial} {Intelligence} {Research}: {Volume} {I}: {Knowledge} {Representation}, {Reasoning} and {Learning}},
publisher = {Springer International Publishing},
author = {Denœux, Thierry and Dubois, Didier and Prade, Henri},
editor = {Marquis, Pierre and Papini, Odile and Prade, Henri},
year = {2020},
doi = {10.1007/978-3-030-06164-7_3},
pages = {69--117},
annote = {Publisher: Springer, Cham},
file = {Denoeux_et_al_2020_Representations_of_Uncertainty_in_AI.pdf:files/5850/Denoeux_et_al_2020_Representations_of_Uncertainty_in_AI.pdf:application/pdf},
}
@article{dubois_practical_2015,
title = {Practical {Methods} for {Constructing} {Possibility} {Distributions}},
volume = {vol. 31},
url = {https://hal.archives-ouvertes.fr/hal-01538306},
doi = {10.1002/int.21782},
abstract = {This survey paper provides an overview of existing methods for building possibility distributions. We both consider the case of qualitative possibility theory, where the scale remains ordinal, and the case of quantitative possibility theory, where the scale is the real interval [0, 1]. Methods may be order-based or similarity-based for qualitative possibility distributions, whereas statistical methods apply in the quantitative case and then possibilities encode nested random epistemic sets or upper bounds of probabilities. But distance-based approaches, or expert estimates, may be also exploited in the quantitative case.},
number = {n° 3},
urldate = {2020-11-04},
journal = {International Journal of Intelligent Systems},
author = {Dubois, Didier and Prade, Henri},
month = sep,
year = {2015},
note = {Number: n° 3
Publisher: Wiley},
keywords = {Constructing, distributions, possibility},
pages = {pp. 215--239},
file = {Dubois_Prade_2015_Practical_Methods_for_Constructing_Possibility_Distributions.pdf:files/5846/Dubois_Prade_2015_Practical_Methods_for_Constructing_Possibility_Distributions.pdf:application/pdf},
}
@article{guberman_complex_2016,
title = {On {Complex} {Valued} {Convolutional} {Neural} {Networks}},
url = {http://arxiv.org/abs/1602.09046},
abstract = {Convolutional neural networks (CNNs) are the cutting edge model for supervised machine learning in computer vision. In recent years CNNs have outperformed traditional approaches in many computer vision tasks such as object detection, image classification and face recognition. CNNs are vulnerable to overfitting, and a lot of research focuses on finding regularization methods to overcome it. One approach is designing task specific models based on prior knowledge. Several works have shown that properties of natural images can be easily captured using complex numbers. Motivated by these works, we present a variation of the CNN model with complex valued input and weights. We construct the complex model as a generalization of the real model. Lack of order over the complex field raises several difficulties both in the definition and in the training of the network. We address these issues and suggest possible solutions. The resulting model is shown to be a restricted form of a real valued CNN with twice the parameters. It is sensitive to phase structure, and we suggest it serves as a regularized model for problems where such structure is important. This suggestion is verified empirically by comparing the performance of a complex and a real network in the problem of cell detection. The two networks achieve comparable results, and although the complex model is hard to train, it is significantly less vulnerable to overfitting. We also demonstrate that the complex network detects meaningful phase structure in the data.},
urldate = {2020-11-04},
journal = {arXiv:1602.09046 [cs]},
author = {Guberman, Nitzan},
month = feb,
year = {2016},
note = {arXiv: 1602.09046},
keywords = {Computer Science - Neural and Evolutionary Computing},
file = {Guberman_2016_On_Complex_Valued_Convolutional_Neural_Networks.pdf:files/5844/Guberman_2016_On_Complex_Valued_Convolutional_Neural_Networks.pdf:application/pdf},
}
@article{stewart_biologically_2011,
series = {The 9th {International} {Conference} on {Cognitive} {Modeling}. {Manchester}, {UK}, {July} 2009},
title = {A biologically realistic cleanup memory: {Autoassociation} in spiking neurons},
volume = {12},
issn = {1389-0417},
shorttitle = {A biologically realistic cleanup memory},
url = {https://linkinghub.elsevier.com/retrieve/pii/S1389041710000525},
doi = {10.1016/j.cogsys.2010.06.006},
abstract = {Methods for “cleaning up” (or recognizing) states of a neural network are crucial for the functioning of many neural cognitive models. This process takes a noisy approximation of a state and recovers the original information. As a particular example, we consider the cleanup required for the use of Vector Symbolic Architectures, which provide a method for manipulating symbols using a fixed-length vector representation. To recognize the result of these manipulations, a mechanism for cleaning up the resulting noisy representation is needed, as this noise increases with the number of symbols being combined. While these symbolic manipulations have previously been modelled with biologically plausible neurons, this paper presents the first spiking neuron model of the cleanup process. We demonstrate that it approaches ideal performance and that the neural requirements scale linearly with the number of distinct symbols in the system. While this result is relevant for any biological model requiring cleanup, it is crucial for VSAs, as it completes the set of mechanisms needed to provide a full neural implementation of symbolic reasoning.},
language = {en},
number = {2},
urldate = {2021-02-02},
journal = {Cognitive Systems Research},
author = {Stewart, Terrence C. and Tang, Yichuan and Eliasmith, Chris},
month = jun,
year = {2011},
keywords = {Auto-associative memory, Holographic reduced representation, Neural engineering framework, Vector Symbolic Architectures},
pages = {84--92},
file = {ScienceDirect Snapshot:files/5719/S1389041710000525.html:text/html;Stewart_et_al_2011_A_biologically_realistic_cleanup_memory.pdf:files/5718/Stewart_et_al_2011_A_biologically_realistic_cleanup_memory.pdf:application/pdf},
}
@article{mandler_association_2011,
title = {From {Association} to {Organization}},
volume = {20},
issn = {0963-7214, 1467-8721},
url = {http://journals.sagepub.com/doi/10.1177/0963721411414656},
doi = {10.1177/0963721411414656},
abstract = {Recent as well as historical critiques of association theory, which is based on automatic linking mechanisms, lead to a consideration of an alternative: organization theory.The latter theory postulates that human memory is organized, instead, in a nested, hierarchical fashion that structures storage and retrieval. Organization theory also postulates that there is a limit of four expandable units in organized memory and that the same limit is found in recall and production units.},
language = {en},
number = {4},
urldate = {2021-02-02},
journal = {Current Directions in Psychological Science},
author = {Mandler, George},
month = aug,
year = {2011},
note = {Publisher: SAGE Publications Inc},
keywords = {memory, association theory, memory capacity, organization theory},
pages = {232--235},
file = {Mandler_2011_From_Association_to_Organization.pdf:files/5684/Mandler_2011_From_Association_to_Organization.pdf:application/pdf},
}
@article{eichenbaum_memory_2017,
title = {Memory: {Organization} and {Control}},
volume = {68},
issn = {0066-4308, 1545-2085},
shorttitle = {Memory},
url = {http://www.annualreviews.org/doi/10.1146/annurev-psych-010416-044131},
doi = {10.1146/annurev-psych-010416-044131},
abstract = {A major goal of memory research is to understand how cognitive processes in memory are supported at the level of brain systems and network representations. Especially promising in this direction are new findings in humans and animals that converge in indicating a key role for the hippocampus in the systematic organization of memories. New findings also indicate that the prefrontal cortex may play an equally important role in the active control of memory organization during both encoding and retrieval. Observations about the dialog between the hippocampus and prefrontal cortex provide new insights into the operation of the larger brain system that serves memory.},
language = {en},
number = {1},
urldate = {2021-02-02},
journal = {Annual Review of Psychology},
author = {Eichenbaum, Howard},
month = jan,
year = {2017},
pages = {19--45},
file = {Eichenbaum_2017_Memory.pdf:files/5745/Eichenbaum_2017_Memory.pdf:application/pdf;Snapshot:files/5744/annurev-psych-010416-044131.html:text/html},
}
@article{schlegel_comparison_2020,
title = {A comparison of {Vector} {Symbolic} {Architectures}},
url = {http://arxiv.org/abs/2001.11797},
abstract = {Vector Symbolic Architectures (VSAs) combine a high-dimensional vector space with a set of carefully designed operators in order to perform symbolic computations with large numerical vectors. Major goals are the exploitation of their representational power and ability to deal with fuzziness and ambiguity. Over the past years, VSAs have been applied to a broad range of tasks and several VSA implementations have been proposed. The available implementations differ in the underlying vector space (e.g., binary vectors or complex-valued vectors) and the particular implementations of the required VSA operators – with important ramifications for the properties of these architectures. For example, not every VSA is equally well suited to address each task, including complete incompatibility. This paper provides an overview of eleven available VSA implementations and discusses their commonalities and differences in the underlying vector space, bundling, and binding/unbinding operations. We create a taxonomy of available binding/unbinding operations and show an important ramification for non self-inverse binding operations using an example from analogical reasoning. A main contribution is the experimental comparison of the available implementations in order to evaluate (1) the capacity of bundles, (2) the approximation quality of non-exact unbinding operations, (3) the influence of combining binding and bundling operations on the query answering performance, and (4) the performance on two example applications: visual place recognition and language recognition. An overall good performance is shown by the Holographic Reduced Representations VSA in the frequency domain (FHRR). However, its non-self-inverse binding mechanism can negatively influence its applicability, e.g. to analogical reasoning. Self-inverting VSAs like MAP or BSC are better suited for such applications. We expect this systematization and comparison to be relevant for development and evaluation of new VSAs, but most importantly, to support the selection of an appropriate VSA for a particular task. The implementations are available in form of a MATLAB toolbox to simplify testing different VSAs for new applications.},
language = {en},
urldate = {2021-02-02},
journal = {arXiv:2001.11797 [cs]},
author = {Schlegel, Kenny and Neubert, Peer and Protzel, Peter},
month = nov,
year = {2020},
note = {arXiv: 2001.11797},
keywords = {Artificial intelligence},
annote = {Comment: 14 pages, 10 figures, preprint - manuscript},
annote = {Includes a complex Holographic Reduced Representation},
file = {Schlegel_et_al_2020_A_comparison_of_Vector_Symbolic_Architectures.pdf:files/5831/Schlegel_et_al_2020_A_comparison_of_Vector_Symbolic_Architectures.pdf:application/pdf},
}
@book{eliasmith_how_2013,
title = {How to {Build} a {Brain}: {A} {Neural} {Architecture} for {Biological} {Cognition}},
isbn = {978-0-19-979454-6},
shorttitle = {How to {Build} a {Brain}},
abstract = {One goal of researchers in neuroscience, psychology, and artificial intelligence is to build theoretical models that are able to explain the flexibility and adaptiveness of biological systems. How to build a brain provides a detailed guided exploration of a new cognitive architecture that takes biological detail seriously, while addressing cognitive phenomena. The Semantic Pointer Architecture (SPA) introduced in this book provides a set of tools for constructing a wide range of biologically constrained perceptual, cognitive, and motor models. Examples of such models are provided, and they are shown to explain a wide range of data including single cell recordings, neural population activity, reaction times, error rates, choice behavior, and fMRI signals. Each of these models introduces a major feature of biological cognition addressed in the book, including semantics, syntax, control, learning, and memory. These models are not introduced as independent considerations of brain function, but instead integrated to give rise to what is currently the world's largest functional brain model. The last half of this book compares the Semantic Pointer Architecture with the current state-of-the-art, addressing issues of theory construction in the behavioral sciences, semantic compositionality, and scalability, among other considerations. The book concludes with a discussion of conceptual challenges raised by this architecture, and identifies several outstanding challenges for this, and other, cognitive architectures. Along the way, the book considers neural coding, concept representation, neural dynamics, working memory, neuroanatomy, reinforcement learning, and spike-timing dependent plasticity. The book includes 8 detailed, hands-on tutorials exploiting the free Nengo neural simulation environment, providing practical experience with the concepts and models presented throughout.},
language = {en},
publisher = {OUP USA},
author = {Eliasmith, Chris},
month = jun,
year = {2013},
note = {Google-Books-ID: BK0YRJPmuzgC},
keywords = {Psychology / Cognitive Psychology \& Cognition},
annote = {Google-Books-ID: BK0YRJPmuzgC},
}
@article{alexandre_quelles_2019,
title = {De quelles façons l’intelligence artificielle se sert-elle des neurosciences ?},
url = {https://hal.inria.fr/hal-03085820},
abstract = {L’Intelligence Artificielle (IA) s’est construite sur une opposition entre connaissances et données. Les neurosciences ont fourni des éléments confortant cette vision mais ont aussi révélé que des propriétés importantes de notre cognition reposent sur des interdépendances fortes entre ces deux concepts. Cependant l’IA reste bloquée sur ses conceptions initiales et ne pourra plus participer à cette dynamique vertueuse tant qu’elle n’aura pas intégré cette vision différenciée.},
language = {fr},
urldate = {2020-12-22},
journal = {The Conversation},
author = {Alexandre, Frédéric},
month = oct,
year = {2019},
file = {Alexandre_2019_De_quelles_facons_l’intelligence_artificielle_se_sert-elle_des_neurosciences.pdf:files/5756/Alexandre_2019_De_quelles_facons_l’intelligence_artificielle_se_sert-elle_des_neurosciences.pdf:application/pdf;Snapshot:files/6686/hal-03085820.html:text/html},
}
@article{ayadi_ontology_2019,
series = {Knowledge-{Based} and {Intelligent} {Information} \& {Engineering} {Systems}: {Proceedings} of the 23rd {International} {Conference} {KES2019}},
title = {Ontology population with deep learning-based {NLP}: a case study on the {Biomolecular} {Network} {Ontology}},
volume = {159},
issn = {1877-0509},
shorttitle = {Ontology population with deep learning-based {NLP}},
url = {http://www.sciencedirect.com/science/article/pii/S1877050919313961},
doi = {10.1016/j.procs.2019.09.212},
abstract = {As a scientific discipline, systems biology aims to build models of biological systems and processes through the computer analysis of a large amount of experimental data describing the behaviour of whole cells. It is within this context that we already developed the Biomolecular Network Ontology especially for the semantic understanding of the behaviour of complex biomolecular networks and their transittability. However, the challenge now is how to automatically populate it from a variety of biological documents. To this end, the target of this paper is to propose a new approach to automatically populate the Biomolecular Network Ontology and take advantage of the vast amount of biological knowledge expressed in heterogeneous unstructured data about complex biomolecular networks. Indeed, we have recently observed the emergence of deep learning techniques that provide significant and rapid progress in several domains, particularly in the process of deriving high-quality information from text. Despite its significant progress in recent years, deep learning is still not commonly used to populate ontologies. In this paper, we present a deep learning-based NLP ontology population system to populate the Biomolecular Network Ontology. Its originality is to jointly exploit deep learning and natural language processing techniques to identify, extract and classify new instances referring to the BNO ontology’s concepts from textual data. The preliminary results highlight the efficiency of our proposal for ontology population.},
language = {en},
urldate = {2020-10-04},
journal = {Procedia Computer Science},
author = {Ayadi, Ali and Samet, Ahmed and de Beuvron, François de Bertrand and Zanni-Merk, Cecilia},
month = jan,
year = {2019},
keywords = {Deep learning, Biomolecular Network Ontology, Knowledge acquisition, Natural language processing, Ontology population},
pages = {572--581},
file = {Ayadi_et_al_2019_Ontology_population_with_deep_learning-based_NLP.pdf:files/5689/Ayadi_et_al_2019_Ontology_population_with_deep_learning-based_NLP.pdf:application/pdf;Snapshot:files/5751/S1877050919313961.html:text/html},
}
@article{chui_deep_2018,
title = {Deep {Nets} for {Local} {Manifold} {Learning}},
volume = {4},
issn = {2297-4687},
url = {https://www.frontiersin.org/articles/10.3389/fams.2018.00012/full},
doi = {10.3389/fams.2018.00012},
abstract = {The problem of extending a function \$f\$ defined on a training data \${\textbackslash}mathcal\{C\}\$ on an unknown manifold \${\textbackslash}mathbb\{X\}\$ to the entire manifold and a tubular neighborhood of this manifold is considered in this paper. For \${\textbackslash}mathbb\{X\}\$ embedded in a high dimensional ambient Euclidean space \${\textbackslash}mathbb\{\vphantom{\}}R{\textbar}{\textasciicircum}D\$, a deep learning algorithm is developed for finding a local coordinate system for the manifold {\textbackslash}textbf\{without eigen--decomposition\}, which reduces the problem to the classical problem of function approximation on a low dimensional cube. Deep nets (or multilayered neural networks) are proposed to accomplish this approximation scheme by using the training data. Our methods do not involve such optimization techniques as back--propagation, while assuring optimal (a priori) error bounds on the output in terms of the number of derivatives of the target function. In addition, these methods are universal, in that they do not require a prior knowledge of the smoothness of the target function, but adjust the accuracy of approximation locally and automatically, depending only upon the local smoothness of the target function. Our ideas are easily extended to solve both the pre--image problem and the out--of--sample extension problem, with a priori bounds on the growth of the function thus extended.},
language = {English},
urldate = {2020-10-04},
journal = {Frontiers in Applied Mathematics and Statistics},
author = {Chui, Charles K. and Mhaskar, Hrushikesh N.},
year = {2018},
note = {Publisher: Frontiers},
keywords = {deep learning, Function Approximation, Local approximation, Manifold Learning, neural networks},
annote = {Publisher: Frontiers},
file = {Chui_Mhaskar_2018_Deep_Nets_for_Local_Manifold_Learning.pdf:files/5708/Chui_Mhaskar_2018_Deep_Nets_for_Local_Manifold_Learning.pdf:application/pdf},
}
@inproceedings{gayler_vector_2003,
title = {Vector {Symbolic} {Architectures} answer {Jackendoff}'s challenges for cognitive neuroscience},
abstract = {Jackendoff (2002) posed four challenges that linguistic combinatoriality and rules of language present to theories of brain function. The essence of these problems is the question of how to neurally instantiate the rapid construction and transformation of the compositional structures that are typically taken to be the domain of symbolic processing. He contended that typical connectionist approaches fail to meet these challenges and that the dialogue between linguistic theory and cognitive neuroscience will be relatively unproductive until the importance of these problems is widely recognised and the challenges answered by some technical innovation in connectionist modelling. This paper claims that a little-known family of connectionist models (Vector Symbolic Architectures) are able to meet Jackendoff’s challenges.},
booktitle = {Frontiers in {Artificial} {Intelligence} and {Applications}},
author = {Gayler, Ross},
month = jan,
year = {2003},
note = {Journal Abbreviation: ICCS/ASCS International Conference on Cognitive Science
Publication Title: ICCS/ASCS International Conference on Cognitive Science},
annote = {Journal Abbreviation: ICCS/ASCS International Conference on Cognitive Science Publication Title: ICCS/ASCS International Conference on Cognitive Science},
file = {Gayler_2003_Vector_Symbolic_Architectures_answer_Jackendoff's_challenges_for_cognitive.pdf:files/5739/Gayler_2003_Vector_Symbolic_Architectures_answer_Jackendoff's_challenges_for_cognitive.pdf:application/pdf},
}
@inproceedings{jimenez_sound_2018,
title = {Sound event classification using ontology-based neural networks},
abstract = {State of the art sound event classification relies in neural networks to learn the associations between class labels and audio recordings within a dataset. These datasets typically define an ontology to create a structure that relates these sound classes with more abstract super classes. Hence, the ontology serves as a source of domain knowledge representation of sounds. However, the ontology information is rarely considered, and specially under explored to model neural network architectures. We propose two ontology-based neural network architectures for sound event classification. We defined a framework to design simple network architectures that preserve an ontological structure. The networks are trained and evaluated using two of the most common sound event classification datasets. Results show an improvement in classification performance demonstrating the benefits of including the ontological information.},
language = {en},
booktitle = {Proceedings of the {Annual} {Conference} on {Neural} {Information} {Processing} {Systems}},
author = {Jiménez, Abelino and Elizalde, Benjamin and Raj, Bhiksha},
year = {2018},
pages = {9},
file = {Jimenez_et_al_2018_Sound_event_classification_using_ontology-based_neural_networks.pdf:files/5686/Jimenez_et_al_2018_Sound_event_classification_using_ontology-based_neural_networks.pdf:application/pdf},
}
@phdthesis{nallapu_closed_2019,
type = {These de doctorat},
title = {A closed loop framework of decision-making and learning in primate prefrontal circuits.},
copyright = {Licence Etalab},
url = {https://www.theses.fr/2019BORD0300},
abstract = {Cette thèse propose de construire un cadre de travail de modélisation systémique, pour aider à la compréhension de l'organisation des systèmes associant le cortex préfrontal (PFC) et les ganglions de la base (BG) et de leurs interactions fonctionnelles dans les processus de prise de décision et de comportement dirigé par les buts chez les humains. Un environnement de jeu vidéo, Minecraft, est utilisé pour concevoir des expériences. Elles visent à tester le jeu vidéo dans un environnement qui pourrait être plus complexe et réaliste, si besoin. Ce cadre, avec l'expérimentation virtuelle, forme une architecture en boucle fermée pour l'étude de comportements animaux de haut niveau. Le cadre des systèmes neuronaux de ce travail repose sur la dynamique des réseaux entre des sous-systèmes du PFC et des BG. Le PFC joue un rôle crucial dans les fonctions exécutives comme la planification, l'attention, le comportement dirigé par les buts, etc. Les BG sont un groupe de noyaux sous-corticaux qui ont fait l'objet d'études approfondies dans le domaine du contrôle moteur et de la sélection de l'action. Différentes régions dans le PFC et les structures au sein des BG sont organisées anatomiquement, en boucles parallèles et séparées (chacune d'entre elles étant appelée une boucle CBG). Ces boucles peuvent être, à un niveau abstrait, divisées en 3 types : les boucles limbiques, les boucles associatives et les boucles sensorimotrices. Tout d'abord, un cadre global avec ces boucles parallèles a été mis en oeuvre. L'accent est mis sur les boucles limbiques. Les boucles associatives et sensori-motrices sont modélisées de manière algorithmique, à l'aide de la plate-forme d'expérimentation pour le contrôle moteur. Pour ce qui concerne les boucles limbiques, le cortex orbitofrontal (OFC) représente une boucle pour estimer les préférences et la boucle du cortex cingulaire antérieur (ACC) représente les besoins internes. Le substrat correspondant de ces boucles dans les BG est le striatum ventral (VS), beaucoup étudié pour son rôle dans le codage des valeurs. Des scénarios simples sont conçus dans l'environnement virtuel en utilisant l'agent, certains objets et des récompenses appétitives dans l'environnement. Les boucles limbiques ont été implémentées selon des modèles existants de prise de décision dans les BG. Ainsi, le cadre théorique et la plateforme expérimentale servent de banc d'essai pour ces modèles spécifiques qui doivent s'adapter dans une perspective plus large. Ensuite, nous utilisons ce cadre pour étudier de plus près le rôle de l’OFC dans la prise de décision guidée par la valeur et le comportement dirigé par les buts. Dans le cadre de cette thèse, des observations importantes sur le rôle de l’OFC dans le comportement ont été intégrées en consolidant de nombreuses données expérimentales. [...]},
language = {en},
urldate = {2020-12-22},
school = {Bordeaux},
author = {Nallapu, Bhargav Teja},
collaborator = {Alexandre, Frédéric and Viéville, Thierry},
month = dec,
year = {2019},
keywords = {Learning, Prefrontal cortex, Comportement vers un but, Cortex préfrontal, Cortex préfrontale, Decision-Making, Expérimentation virtuelle, Goal-Directed behaviour, Modélisation computationnelle, Modélisation des données (informatique), Prise de décision, Prise de décision -- Simulation par ordinateur, Virtual Experimentation, Prise de décision – Simulation par ordinateur, Virtual Experimentation, Computational modelling},
annote = {Sous la direction de Frédéric Alexandre et de Thierry Viéville. Soutenue le 05-12-2019,à Bordeaux , dans le cadre de École doctorale de mathématiques et informatique (Talence, Gironde) , en partenariat avec Laboratoire bordelais de recherche en informatique (laboratoire) et de Institut des Maladies Neurodégénératives (laboratoire) .},
file = {Nallapu_2019_A_closed_loop_framework_of_decision-making_and_learning_in_primate_prefrontal.pdf:files/5729/Nallapu_2019_A_closed_loop_framework_of_decision-making_and_learning_in_primate_prefrontal.pdf:application/pdf;Snapshot:files/5730/tel-02878358.html:text/html},
}
@article{pulvermuller_how_2013,
title = {How neurons make meaning: brain mechanisms for embodied and abstract-symbolic semantics},
volume = {17},
issn = {1364-6613},
shorttitle = {How neurons make meaning},
url = {http://www.sciencedirect.com/science/article/pii/S1364661313001228},
doi = {10.1016/j.tics.2013.06.004},
abstract = {How brain structures and neuronal circuits mechanistically underpin symbolic meaning has recently been elucidated by neuroimaging, neuropsychological, and neurocomputational research. Modality-specific ‘embodied’ mechanisms anchored in sensorimotor systems appear to be relevant, as are ‘disembodied’ mechanisms in multimodal areas. In this paper, four semantic mechanisms are proposed and spelt out at the level of neuronal circuits: referential semantics, which establishes links between symbols and the objects and actions they are used to speak about; combinatorial semantics, which enables the learning of symbolic meaning from context; emotional-affective semantics, which establishes links between signs and internal states of the body; and abstraction mechanisms for generalizing over a range of instances of semantic meaning. Referential, combinatorial, emotional-affective, and abstract semantics are complementary mechanisms, each necessary for processing meaning in mind and brain.},
language = {en},
number = {9},
urldate = {2020-12-21},
journal = {Trends in Cognitive Sciences},
author = {Pulvermüller, Friedemann},
month = sep,
year = {2013},
pages = {458--470},
file = {Pulvermuller_2013_How_neurons_make_meaning.pdf:files/5724/Pulvermuller_2013_How_neurons_make_meaning.pdf:application/pdf;ScienceDirect Snapshot:files/5723/S1364661313001228.html:text/html},
}
@inproceedings{simpkin_scalable_2018,
address = {Venice, Italy},
title = {A {Scalable} {Vector} {Symbolic} {Architecture} {Approach} for {Decentralized} {Workflows}},
url = {http://orca.cf.ac.uk/112242/},
abstract = {Vectors Symbolic Architectures (VSAs) are distributed representations that combine random patterns, representing atomic symbols across a hyper-dimensional vector space, into new symbolic vector representations that semantically represent the component vectors and their relationships. In this paper, we extend the VSA approach and apply it to decentralized workflows, capable of executing distributed compute nodes and their interdependencies. To achieve this goal, services must be discovered and orchestrated in a decentralized way with the minimum communication overhead whilst providing detailed information about the workflow - tasks, dependencies, location, metadata, and so on. To this end, we extended VSAs using a hierarchical vector chunking scheme that enables semantic matching at each level and provides scaling up to tens of thousands of services. We then show how VSAs can be used to encode complex workflows by building primitives that represent sequences (pipelines) and then extend this to support full Directed Acyclic Graphs (DAGs) and apply this to five well-known Pegasus scientific workflows to demonstrate the approach},
language = {en},
urldate = {2020-12-21},
author = {Simpkin, Christopher and Taylor, Ian and Bent, Graham and de Mel, Geeth and Ganti, Raghu},
month = may,
year = {2018},
file = {Simpkin_et_al_2018_A_Scalable_Vector_Symbolic_Architecture_Approach_for_Decentralized_Workflows.pdf:files/5681/Simpkin_et_al_2018_A_Scalable_Vector_Symbolic_Architecture_Approach_for_Decentralized_Workflows.pdf:application/pdf},
}
@article{xiao_one_2015,
title = {From one point to a manifold: {Knowledge} graph embedding for precise link prediction},
journal = {arXiv preprint arXiv:1512.04792},
author = {Xiao, Han and Huang, Minlie and Zhu, Xiaoyan},
year = {2015},
file = {Xiao_et_al_2015_From_one_point_to_a_manifold.pdf:files/5716/Xiao_et_al_2015_From_one_point_to_a_manifold.pdf:application/pdf},
}
@article{zhu_ldmnet_2017,
title = {{LDMNet}: {Low} {Dimensional} {Manifold} {Regularized} {Neural} {Networks}},
shorttitle = {{LDMNet}},
url = {http://arxiv.org/abs/1711.06246},
abstract = {Deep neural networks have proved very successful on archetypal tasks for which large training sets are available, but when the training data are scarce, their performance suffers from overfitting. Many existing methods of reducing overfitting are data-independent, and their efficacy is often limited when the training set is very small. Data-dependent regularizations are mostly motivated by the observation that data of interest lie close to a manifold, which is typically hard to parametrize explicitly and often requires human input of tangent vectors. These methods typically only focus on the geometry of the input data, and do not necessarily encourage the networks to produce geometrically meaningful features. To resolve this, we propose a new framework, the Low-Dimensional-Manifold-regularized neural Network (LDMNet), which incorporates a feature regularization method that focuses on the geometry of both the input data and the output features. In LDMNet, we regularize the network by encouraging the combination of the input data and the output features to sample a collection of low dimensional manifolds, which are searched efficiently without explicit parametrization. To achieve this, we directly use the manifold dimension as a regularization term in a variational functional. The resulting Euler-Lagrange equation is a Laplace-Beltrami equation over a point cloud, which is solved by the point integral method without increasing the computational complexity. We demonstrate two benefits of LDMNet in the experiments. First, we show that LDMNet significantly outperforms widely-used network regularizers such as weight decay and DropOut. Second, we show that LDMNet can be designed to extract common features of an object imaged via different modalities, which proves to be very useful in real-world applications such as cross-spectral face recognition.},
urldate = {2020-10-04},
journal = {arXiv:1711.06246 [cs]},
author = {Zhu, Wei and Qiu, Qiang and Huang, Jiaji and Calderbank, Robert and Sapiro, Guillermo and Daubechies, Ingrid},
month = nov,
year = {2017},
note = {arXiv: 1711.06246
version: 1},
keywords = {Computer Vision and Pattern Recognition},
annote = {arXiv: 1711.06246 version: 1},
file = {Zhu_et_al_2017_LDMNet.pdf:files/5715/Zhu_et_al_2017_LDMNet.pdf:application/pdf},
}
@inproceedings{voelker_learning_2014,
title = {Learning large-scale heteroassociative memories in spiking neurons},
doi = {10.13140/RG.2.1.1382.1688},
abstract = {Associative memories have been an active area of research over the last forty years (Willshaw et al., 1969; Kohonen, 1972; Hopfield, 1982) because they form a central component of many cognitive architectures (Pollack, 1988; Anderson \& Lebiere, 1998). We focus specifically on associative memories that store associations between arbitrary pairs of neural states. When a noisy version of an input state vector is presented to the network, it must output a ”clean” version of the associated state vector. We describe a method for building large-scale networks for online learning of associations using spiking neurons, which works by exploiting the techniques of the Neural Engineering Framework (Eliasmith \& Anderson, 2003). This framework has previously been used by Stewart et al. (2011) to create memories that possess a number of desirable properties including high accuracy, a fast, feedforward recall process, and etcient scaling, requiring a number of neurons linear in the number of stored associations. These memories have played a central role in several recent neural cognitive models including Spaun, the world’s largest functional brain model (Eliasmith et al., 2012), as well as a proposal for human-scale, biologically plausible knowledge representation (Crawford et al., 2013). However, these memories are constructed using an ne optimization method that is not biologically plausible. Here we demonstrate how a similar set of connection weights can be arrived at through a biologically plausible, online learning process featuring a novel synaptic learning rule inspired in part by the well-known Oja learning rule (Oja, 1989). We present the details of our method and report the results of simulations exploring the storage capacity of these networks. We show that our technique scales up to large numbers of associations, and that recall performance degrades gracefully as the theoretical capacity is exceeded. This work has been implemented in the Nengo simulation package (http://nengo.ca), which will allow straightforward implementations of spiking neural networks on neuromorphic hardware. The result of our work is a fast, adaptive, scalable associative memory composed of spiking neurons which we expect to be a valuable addition to large systems peforming online neural computation.},
author = {Voelker, Aaron and Crawford, Eric and Eliasmith, Chris},
month = jul,
year = {2014},
doi = {10.13140/RG.2.1.1382.1688},
file = {Voelker_et_al_2014_Learning_large-scale_heteroassociative_memories_in_spiking_neurons.pdf:files/5697/Voelker_et_al_2014_Learning_large-scale_heteroassociative_memories_in_spiking_neurons.pdf:application/pdf},
}
@inproceedings{lallement_neurosymbolic_1995,
title = {Neurosymbolic {Integration}: {Cognitive} {Grounds} and {Computational} {Strategies}},
shorttitle = {Neurosymbolic {Integration}},
abstract = {The ultimate---if implicit---goal of artificial intelligence (AI) research is to model the full range of human cognitive capabilities. Symbolic AI and connectionism, the major AI paradigms, have each tried---and failed---to attain this goal. In the meantime, the idea has gained ground that this goal might still be within reach if we could harness the respective strengths of these two paradigms in integrated neurosymbolic models. This paper attempts to lay a cognitive basis for neurosymbolic integration and describes the different strategies that have been adopted to date. Unified approaches strive to attain symbol-processing capabilities using neural network techniques alone, while hybrid approaches blend symbolic and neural models in novel architectures with the hope of gleaning the best of both paradigms. Keywords: Connectionism, symbolic AI, neurosymbolic integration, hybrid models, connectionist symbol processing 1 Introduction Since its inception, artificial intelligence (AI) ha...},
language = {en},
booktitle = {Proceedings {World} {Conference} on the {Fundamentals} of {Artificial} {Intelligence}},
author = {Lallement, Yannick and Hilario, Melanie and Alexandre, Frederic},
year = {1995},
pages = {12},
file = {Lallement_et_al_1995_Neurosymbolic_Integration.pdf:files/5841/Lallement_et_al_1995_Neurosymbolic_Integration.pdf:application/pdf},
}
@article{bekolay_nengo_2014,
title = {Nengo: a {Python} tool for building large-scale functional brain models},
volume = {7},
issn = {1662-5196},
shorttitle = {Nengo},
url = {http://journal.frontiersin.org/article/10.3389/fninf.2013.00048/abstract},
doi = {10.3389/fninf.2013.00048},
abstract = {Neuroscience currently lacks a comprehensive theory of how cognitive processes can be implemented in a biological substrate. The Neural Engineering Framework (NEF) proposes one such theory, but has not yet gathered significant empirical support, partly due to the technical challenge of building and simulating large-scale models with the NEF. Nengo is a software tool that can be used to build and simulate large-scale models based on the NEF; currently, it is the primary resource for both teaching how the NEF is used, and for doing research that generates specific NEF models to explain experimental data. Nengo 1.4, which was implemented in Java, was used to create Spaun, the world’s largest functional brain model (Eliasmith et al., 2012). Simulating Spaun highlighted limitations in Nengo 1.4’s ability to support model construction with simple syntax, to simulate large models quickly, and to collect large amounts of data for subsequent analysis. This paper describes Nengo 2.0, which is implemented in Python and overcomes these limitations. It uses simple and extendable syntax, simulates a benchmark model on the scale of Spaun 50 times faster than Nengo 1.4, and has a flexible mechanism for collecting simulation results.},
language = {en},
urldate = {2021-02-04},
journal = {Frontiers in Neuroinformatics},
author = {Bekolay, Trevor and Bergstra, James and Hunsberger, Eric and DeWolf, Travis and Stewart, Terrence C. and Rasmussen, Daniel and Choo, Xuan and Voelker, Aaron Russell and Eliasmith, Chris},
year = {2014},
keywords = {simulation, Neuroscience, Control theory, Nengo, neural engineering framework, python, theoretical neuroscience},
file = {Bekolay_et_al_2014_Nengo.pdf:files/5754/Bekolay_et_al_2014_Nengo.pdf:application/pdf},
}
@misc{horridge_practical_2011,
title = {A {Practical} {Guide} {To} {Building} {OWL} {Ontologies} {Using} {Protégé} 4 and {CO}-{ODE} {Tools} {Edition} 1.3},
language = {en},
author = {Horridge, Matthew},
month = mar,
year = {2011},
file = {Horridge_2011_A_Practical_Guide_To_Building_OWL_Ontologies_Using_Protege_4_and_CO-ODE_Tools.pdf:files/5687/Horridge_2011_A_Practical_Guide_To_Building_OWL_Ontologies_Using_Protege_4_and_CO-ODE_Tools.pdf:application/pdf},
}
@article{eliasmith_large-scale_2012,
title = {A {Large}-{Scale} {Model} of the {Functioning} {Brain}},
volume = {338},
copyright = {Copyright © 2012, American Association for the Advancement of Science},
issn = {0036-8075, 1095-9203},
url = {https://science.sciencemag.org/content/338/6111/1202},
doi = {10.1126/science.1225266},
abstract = {A central challenge for cognitive and systems neuroscience is to relate the incredibly complex behavior of animals to the equally complex activity of their brains. Recently described, large-scale neural models have not bridged this gap between neural activity and biological function. In this work, we present a 2.5-million-neuron model of the brain (called “Spaun”) that bridges this gap by exhibiting many different behaviors. The model is presented only with visual image sequences, and it draws all of its responses with a physically modeled arm. Although simplified, the model captures many aspects of neuroanatomy, neurophysiology, and psychological behavior, which we demonstrate via eight diverse tasks.},
language = {en},
number = {6111},
urldate = {2021-02-04},
journal = {Science},
author = {Eliasmith, Chris and Stewart, Terrence C. and Choo, Xuan and Bekolay, Trevor and DeWolf, Travis and Tang, Yichuan and Rasmussen, Daniel},
month = nov,
year = {2012},
pmid = {23197532},
note = {Publisher: American Association for the Advancement of Science
Section: Report},
pages = {1202--1205},
annote = {Publisher: American Association for the Advancement of Science Section: Report},
file = {Eliasmith_et_al_2012_A_Large-Scale_Model_of_the_Functioning_Brain.pdf:files/5743/Eliasmith_et_al_2012_A_Large-Scale_Model_of_the_Functioning_Brain.pdf:application/pdf},
}
@book{sun_connectionist-symbolic_2013,
edition = {3rd edition},
title = {Connectionist-{Symbolic} {Integration}: {From} {Unified} to {Hybrid} {Approaches}},
url = {https://www.taylorfrancis.com/books/9780203763667},
urldate = {2020-02-23},
publisher = {Taylor \& Francis Group},
author = {Sun, Ron and Alexandre, Frederic},
year = {2013},
}
@misc{rusawuk_possibility_2018,
title = {Possibility and {Necessity}: {An} {Introduction} to {Modality}},
shorttitle = {Possibility and {Necessity}},
url = {https://1000wordphilosophy.com/2018/12/08/possibility-and-necessity-an-introduction-to-modality/},
language = {en},
urldate = {2020-09-24},
journal = {1000-Word Philosophy: An Introductory Anthology},
author = {Rusawuk, Andre Leo},
month = dec,
year = {2018},
}
@book{eliasmith_neural_2002,
series = {A {Bradford} {Book}},
title = {Neural {Engineering}:{Computation}, {Representation}, and {Dynamics} in {Neurobiological} {Systems}},
url = {https://mitpress.mit.edu/books/neural-engineering},
abstract = {For years, researchers have used the theoretical tools of engineering to understand neural systems, but much of this work has been conducted in relative isolation. In Neural Engineering, Chris Eliasmith and Charles Anderson provide a synthesis of the disparate approaches current in computational neuroscience, incorporating ideas from neural coding, neural computation, physiology, communications theory, control theory, dynamics, and probability theory. This synthesis, they argue, enables novel theoretical and practical insights into the functioning of neural systems. Such insights are pertinent to experimental and computational neuroscientists and to engineers, physicists, and computer scientists interested in how their quantitative tools relate to the brain.The authors present three principles of neural engineering based on the representation of signals by neural ensembles, transformations of these representations through neuronal coupling weights, and the integration of control theory and neural dynamics. Through detailed examples and in-depth discussion, they make the case that these guiding principles constitute a useful theory for generating large-scale models of neurobiological function. A software package written in MatLab for use with their methodology, as well as examples, course notes, exercises, documentation, and other material, are available on the Web.},
language = {en},
urldate = {2021-02-09},
publisher = {The MIT Press},
author = {Eliasmith, Chris and Anderson, Charles H.},
year = {2002},
note = {Publisher: The MIT Press},
annote = {Publisher: The MIT Press},
}
@inproceedings{grosof_description_2003,
address = {New York, NY, USA},
series = {{WWW} '03},
title = {Description logic programs: combining logic programs with description logic},
isbn = {978-1-58113-680-7},
shorttitle = {Description logic programs},
url = {https://doi.org/10.1145/775152.775160},
doi = {10.1145/775152.775160},
abstract = {We show how to interoperate, semantically and inferentially, between the leading Semantic Web approaches to rules (RuleML Logic Programs) and ontologies (OWL/DAML+OIL Description Logic) via analyzing their expressive intersection. To do so, we define a new intermediate knowledge representation (KR) contained within this intersection: Description Logic Programs (DLP), and the closely related Description Horn Logic (DHL) which is an expressive fragment of first-order logic (FOL). DLP provides a significant degree of expressiveness, substantially greater than the RDF-Schema fragment of Description Logic. We show how to perform DLP-fusion: the bidirectional translation of premises and inferences (including typical kinds of queries) from the DLP fragment of DL to LP, and vice versa from the DLP fragment of LP to DL. In particular, this translation enables one to "build rules on top of ontologies": it enables the rule KR to have access to DL ontological definitions for vocabulary primitives (e.g., predicates and individual constants) used by the rules. Conversely, the DLP-fusion technique likewise enables one to "build ontologies on top of rules": it enables ontological definitions to be supplemented by rules, or imported into DL from rules. It also enables available efficient LP inferencing algorithms/implementations to be exploited for reasoning over large-scale DL ontologies.},
urldate = {2021-02-09},
booktitle = {Proceedings of the 12th international conference on {World} {Wide} {Web}},
publisher = {Association for Computing Machinery},
author = {Grosof, Benjamin N. and Horrocks, Ian and Volz, Raphael and Decker, Stefan},
month = may,
year = {2003},
keywords = {semantic web, description logic, inferencing, information integration, interoperability, knowledge representation, logic programs, model-theoretic semantics, ontologies, RDF, rules, translation, XML},
pages = {48--57},
file = {Grosof_et_al_2003_Description_logic_programs.pdf:files/5703/Grosof_et_al_2003_Description_logic_programs.pdf:application/pdf},
}
@article{alexandre_global_2021,
title = {A global framework for a systemic view of brain modeling},
volume = {8},
issn = {2198-4018, 2198-4026},
url = {https://braininformatics.springeropen.com/articles/10.1186/s40708-021-00126-4},
doi = {10.1186/s40708-021-00126-4},
abstract = {The brain is a complex system, due to the heterogeneity of its structure, the diversity of the functions in which it participates and to its reciprocal relationships with the body and the environment. A systemic description of the brain is presented here, as a contribution to developing a brain theory and as a general framework where specific models in computational neuroscience can be integrated and associated with global information flows and cognitive functions. In an enactive view, this framework integrates the fundamental organization of the brain in sensorimotor loops with the internal and the external worlds, answering four fundamental questions (what, why, where and how). Our survival-oriented definition of behavior gives a prominent role to pavlovian and instrumental conditioning, augmented during phylogeny by the specific contribution of other kinds of learning, related to semantic memory in the posterior cortex, episodic memory in the hippocampus and working memory in the frontal cortex. This framework highlights that responses can be prepared in different ways, from pavlovian reflexes and habitual behavior to deliberations for goal-directed planning and reasoning, and explains that these different kinds of responses coexist, collaborate and compete for the control of behavior. It also lays emphasis on the fact that cognition can be described as a dynamical system of interacting memories, some acting to provide information to others, to replace them when they are not efficient enough, or to help for their improvement. Describing the brain as an architecture of learning systems has also strong implications in Machine Learning. Our biologically informed view of pavlovian and instrumental conditioning can be very precious to revisit classical Reinforcement Learning and provide a basis to ensure really autonomous learning.},
language = {en},
number = {1},
urldate = {2021-02-26},
journal = {Brain Informatics},
author = {Alexandre, Frederic},
month = dec,
year = {2021},
keywords = {Brain modeling, Cognitive functions, Memory system},
pages = {3},
file = {Alexandre_2021_A_global_framework_for_a_systemic_view_of_brain_modeling.pdf:files/5757/Alexandre_2021_A_global_framework_for_a_systemic_view_of_brain_modeling.pdf:application/pdf;Snapshot:files/5758/s40708-021-00126-4.html:text/html},
}
@article{roux_les_2020,
title = {Les hauts de {Otesia}},
url = {https://hal.inria.fr/hal-03089962},
abstract = {Lorsqu'on parle d'intelligence artificielle, surgit très souvent le problème de la définition de ce que cette notion recouvre, en opposition ou en complément à une intelligence dite "humaine". Profitant des travaux sur la formalisation d'une intelligence mécanique et de nombreux outils développés dans ce cadre, abordons la question passionnante de la modélisation de l'intelligence humaine ! Regardons ici comment quelques scientifiques essayent d'aborder cette question.},
language = {fr},
urldate = {2021-03-02},
journal = {Binaire},
author = {Roux, Lisa and Romero, Margarida and Alexandre, Frédéric and Viéville, Thierry},
month = dec,
year = {2020},
file = {Roux_et_al_2020_Les_hauts_de_Otesia.pdf:files/5722/Roux_et_al_2020_Les_hauts_de_Otesia.pdf:application/pdf;Snapshot:files/5721/hal-03089962.html:text/html},
}
@article{wing_computational_2006,
title = {Computational thinking},
volume = {49},
issn = {0001-0782},
url = {https://doi.org/10.1145/1118178.1118215},
doi = {10.1145/1118178.1118215},
abstract = {It represents a universally applicable attitude and skill set everyone, not just computer scientists, would be eager to learn and use.},
number = {3},
urldate = {2021-03-03},
journal = {Communications of the ACM},
author = {Wing, Jeannette M.},
month = mar,
year = {2006},
pages = {33--35},
file = {Wing_2006_Computational_thinking.pdf:files/5717/Wing_2006_Computational_thinking.pdf:application/pdf},
}
@misc{alexandre_open_2020,
title = {Open {Educational} {Resources} and {MOOC} for {Citizen} {Understanding} of {Artificial} {Intelligence}},
url = {https://hal.inria.fr/hal-03024034},
abstract = {Our whole society is, and will be, deeply impacted by digital technologies and practices. This impact is taking a new qualitative and quantitative turn with what is named artificial intelligence (AI). We must allow everyone to master, thus understand and develop a creative and critical perspective and agency in the way AI is integrated in the different domains of our lives. We have built and now operate a citizen MOOC in AI in the broad sense, on AI foundations and applications, intended for a large public beyond the school domain, with more than 15000 participants engaged in the MOOC after three months. We report here on this project, detailing the didactic choices (linking everyday life elements to fundamental concepts, understanding the "how it works" via online or unplugged concrete activities, making explicit how understanding the "science underneath" allows to better discuss the societal impacts) and the pedagogical method (e.g.: small conceptual videos, contaminating activities to be redone in real life, ...). We finally share learning analytics, quantitative and qualitative evaluations and explain to which extent educational science research helps enlighten such large scale initiatives.},
language = {en},
urldate = {2021-03-03},
author = {Alexandre, Frédéric and Becker, Jade and Comte, Marie-Hélène and Lagarrigue, Aurelie and Liblau, Romain and Romero, Margarida and Viéville, Thierry},
month = jul,
year = {2020},
file = {Alexandre_et_al_2020_Open_Educational_Resources_and_MOOC_for_Citizen_Understanding_of_Artificial.pdf:files/5752/Alexandre_et_al_2020_Open_Educational_Resources_and_MOOC_for_Citizen_Understanding_of_Artificial.pdf:application/pdf;Snapshot:files/5753/hal-03024034.html:text/html},
}
@article{forestier_intrinsically_2020,
title = {Intrinsically {Motivated} {Goal} {Exploration} {Processes} with {Automatic} {Curriculum} {Learning}},
url = {http://arxiv.org/abs/1708.02190},
abstract = {Intrinsically motivated spontaneous exploration is a key enabler of autonomous lifelong learning in human children. It enables the discovery and acquisition of large repertoires of skills through self-generation, self-selection, self-ordering and self-experimentation of learning goals. We present an algorithmic approach called Intrinsically Motivated Goal Exploration Processes (IMGEP) to enable similar properties of autonomous or self-supervised learning in machines. The IMGEP algorithmic architecture relies on several principles: 1) self-generation of goals, generalized as fitness functions; 2) selection of goals based on intrinsic rewards; 3) exploration with incremental goal-parameterized policy search and exploitation of the gathered data with a batch learning algorithm; 4) systematic reuse of information acquired when targeting a goal for improving towards other goals. We present a particularly efficient form of IMGEP, called Modular Population-Based IMGEP, that uses a population-based policy and an object-centered modularity in goals and mutations. We provide several implementations of this architecture and demonstrate their ability to automatically generate a learning curriculum within several experimental setups including a real humanoid robot that can explore multiple spaces of goals with several hundred continuous dimensions. While no particular target goal is provided to the system, this curriculum allows the discovery of skills that act as stepping stone for learning more complex skills, e.g. nested tool use. We show that learning diverse spaces of goals with intrinsic motivations is more efficient for learning complex skills than only trying to directly learn these complex skills.},
language = {en},
urldate = {2021-03-04},
journal = {arXiv:1708.02190 [cs]},
author = {Forestier, Sébastien and Portelas, Rémy and Mollard, Yoan and Oudeyer, Pierre-Yves},
month = jul,
year = {2020},
note = {arXiv: 1708.02190},
keywords = {Artificial intelligence, Machine Learning},
file = {arXiv.org Snapshot:files/5741/1708.html:text/html;Forestier_et_al_2020_Intrinsically_Motivated_Goal_Exploration_Processes_with_Automatic_Curriculum.pdf:files/5740/Forestier_et_al_2020_Intrinsically_Motivated_Goal_Exploration_Processes_with_Automatic_Curriculum.pdf:application/pdf},
}
@article{huang_critical_2020,
title = {A critical review of literature on “unplugged” pedagogies in {K}-12 computer science and computational thinking education},
volume = {0},
issn = {0899-3408},
url = {https://doi.org/10.1080/08993408.2020.1789411},
doi = {10.1080/08993408.2020.1789411},
abstract = {Background and Context Computational thinking (CT) is considered as a valuable literacy for all students, and its inclusion in compulsory schooling could increase the numbers of underrepresented students who pursue computing-related careers. Computer Science Unplugged (CSU) had success in making computer science (CS) accessible to K–12 students in outreach settings. Such “unplugged” approaches have the potential to do the same in formal education. Objective This review considers how research findings on unplugged pedagogies might advance CS/CT education priorities, while highlighting areas of unknown and tension. Method We conducted a search in academic databases using terms +unplugged “computer science” and +unplugged CT, and related terms. Findings We synthesized our review with existing ones to inform the priorities of CS-for-all and CT development. We surfaced CSU’s limitations to broaden access for underrepresented students and suggested a remedy. We proposed 10 research questions that fill key gaps to support efforts that provide just access to quality CS/CT education.},
number = {0},
urldate = {2020-12-03},
journal = {Computer Science Education},
author = {Huang, Wendy and Looi, Chee-Kit},
month = jul,
year = {2020},
note = {Publisher: Routledge
\_eprint: https://doi.org/10.1080/08993408.2020.1789411},
keywords = {Computational thinking, computer science education, equity, schools, unplugged},
pages = {1--29},
file = {Snapshot:files/5735/08993408.2020.html:text/html},
}
@book{engestrom_learning_1987,
address = {Helsinki},
title = {Learning by {Expanding}: {An} {Activity} {Theoretical} {Approach} to {Developmental} {Research}.},
publisher = {Orienta-Konsultit},
author = {Engestrom, Yrjö},
year = {1987},
}
@article{axtell_shopfloor_2000,
title = {Shopfloor innovation: {Facilitating} the suggestion and implementation of ideas},
volume = {73},
issn = {09631798},
shorttitle = {Shopfloor innovation},
url = {http://doi.wiley.com/10.1348/096317900167029},
doi = {10.1348/096317900167029},
language = {en},
number = {3},
urldate = {2020-11-16},
journal = {Journal of Occupational and Organizational Psychology},
author = {Axtell, C. M. and Holman, D. J. and Unsworth, K. L. and Wall, T. D. and Waterson, P. E. and Harrington, E.},
month = sep,
year = {2000},
note = {Number: 3},
pages = {265--285},
file = {Axtell_et_al_2000_Shopfloor_innovation.pdf:files/5786/Axtell_et_al_2000_Shopfloor_innovation.pdf:application/pdf},
}
@phdthesis{gosmann_integrated_2018,
type = {{PhD} {Thesis}},
title = {An {Integrated} {Model} of {Context}, {Short}-{Term}, and {Long}-{Term} {Memory}},
url = {https://uwspace.uwaterloo.ca/handle/10012/13498},
abstract = {I present the context-unified encoding (CUE) model, a large-scale spiking neural network model of human memory.
It combines and integrates activity-based short-term memory with weight-based long-term memory.
The implementation with spiking neurons ensures biological plausibility and allows for predictions on the neural level.
At the same time, the model produces behavioural outputs that have been matched to human data from serial and free recall experiments.
In particular, well-known results such as primacy, recency, transposition error gradients, and forward recall bias have been reproduced with good quantitative matches.
Additionally, the model accounts for the effects of the acetylcholine antagonist scopolamine, and the Hebb repetition effect.
The CUE model combines and extends the ordinal serial encoding (OSE) model, a spiking neuron model of short-term memory, and the temporal context model (TCM), a mathematical model of free recall.
To the former, a neural mechanism for tracking the list position is added.
The latter is converted into a spiking neural network under considerations of the main features and simplification of equations where appropriate.
Previous models of the recall process in the TCM are replaced by a new independent accumulator recall process that is more suited to the integration into a large-scale network.
To implement the modification of the required association matrices, a novel learning rule, the association matrix learning rule (AML), is derived that allows for one-shot learning without catastrophic forgetting.
Its biological plausibility is discussed and it is shown that it accounts for changes in neural firing observed in human recordings from an association learning experiment.
Furthermore, I discuss a recent proposal of an optimal fuzzy temporal memory as replacement for the TCM context signal and show it to be likely to require more neurons than there are in the human brain.
To construct the CUE model, I have used the Neural Engineering Framework (NEF) and Semantic Pointer Architecture (SPA).
This thesis makes novel contributions to both.
I propose to distribute NEF intercepts according to the distribution of cosine similarities of random uniformly distributed unit vectors.
This leads to a uniform distribution of active neurons and reduces the error introduced by spiking noise considerably in high-dimensional neuronal representations.
It improves the asymptotic scaling of the noise error with dimensions d from O(d) to O(d{\textasciicircum}(3/4))\$.
These results are applied to achieve improved Semantic Pointer representations in neural networks are on par with or better than previous methods of optimizing neural representations for the Semantic Pointer Architecture.
Furthermore, the vector-derived transformation binding (VTB) is investigated as an alternative to circular convolution in the SPA, with promising results.},
language = {en},
school = {University of Waterloo (CA)},
author = {Gosmann, Jan},
month = jul,
year = {2018},
note = {Accepted: 2018-07-27T20:24:12Z
Publisher: University of Waterloo},
file = {Gosmann_2018_An_Integrated_Model_of_Context,_Short-Term,_and_Long-Term_Memory.pdf:files/5688/Gosmann_2018_An_Integrated_Model_of_Context,_Short-Term,_and_Long-Term_Memory.pdf:application/pdf;Snapshot:files/5738/13498.html:text/html},
}
@techreport{roux_developpement_2020,
type = {report},
title = {Développement d'une ontologie pour l'analyse d'observables de l'apprenant dans le contexte d'une tâche avec des robots modulaires},
url = {https://hal.inria.fr/hal-03013685},
abstract = {Le but de ce document est de présenter la conception d'une ontologie permettant de réaliser une modélisation de la personne apprenante, de la tâche et des observables au cours de l'activité, ceci afin de développer un modèle applicable aux traces d'apprentissage qui puisse être exploité pour les analyser avec des approches computationnelles. L'enjeu est ici de travailler à partir d'un relativement petit lot de données (quelques dizaines à comparer aux milliers de données utilisées avec les méthodes statistiques classiques), fortement structurées, donc d'introduire un maximum d'informations a priori en amont de l'analyse pour permettre que les résultats soient significatifs. L'apprenant·e est modélisé·e à partir de connaissances issues des sciences de l'éducation et des neurosciences cognitives, y compris les formalismes d'apprentissage machine, dans le cadre très précis d'une tâche -dite « CreaCube »- d'initiation à la pensée informatique, présentée sous forme d'un problème ouvert, qui implique la résolution d'un problème et de faire appel à la créativité. Ce document présente ces éléments et discute les problématiques d'exploration et exploitation, les différents buts (par exemple de performance, de célérité ou de maîtrise de la tâche), avant de relier cela aux différents types de mémoire et de discuter les bases de la résolution de problèmes, et l'engagement dans une activité d'apprentissage. Il décrit ensuite la construction très précise d'une ontologie qui formalise ce processus de résolution de tâche et de construction de connaissances, prenant en compte les stimuli reçus, la découverte d'affordances, la pose d'hypothèses, bien distinguées de la notion de croyance, sans oublier les connaissances contextuelles. La production est mise en partage sous forme de ressource libre et ouverte, et on discute en conclusion à la fois les implications et les perspectives de ce travail pionnier de formalisation d'une telle tâche d'apprentissage humain. Ce rapport de recherche et l'ontologie correspond au travail de recherche de Lisa Roux, qui est aussi la principale autrice du document, encadrée par Margarida Romero et Frédéric Alexandre et a été réalisé dans le cadre du projet Aex AIDE soutenu par Otesia, l'Observatoire des impacts Technologiques, Économiques et Sociétaux de l'Intelligence Artificielle et du numérique.},
language = {fr},
urldate = {2020-12-22},
institution = {Inria},
author = {Roux, Lisa and Romero, Margarida and Alexandre, Frédéric and Viéville, Thierry and Mercier, Chloé},
month = nov,
year = {2020},
pages = {48},
file = {Roux_et_al_2020_Developpement_d'une_ontologie_pour_l'analyse_d'observables_de_l'apprenant_dans.pdf:files/5748/Roux_et_al_2020_Developpement_d'une_ontologie_pour_l'analyse_d'observables_de_l'apprenant_dans.pdf:application/pdf;Snapshot:files/5749/hal-03013685v2.html:text/html},
}
@phdthesis{choo_spaun_2018,
type = {{PhD} {Thesis}},
title = {Spaun 2.0: {Extending} the {World}’s {Largest} {Functional} {Brain} {Model}},
shorttitle = {Spaun 2.0},
url = {https://uwspace.uwaterloo.ca/handle/10012/13308},
abstract = {Building large-scale brain models is one method used by theoretical neuroscientists to understand the way the human brain functions. Researchers typically use either a bottom-up approach, which focuses on the detailed modelling of various biological properties of the brain and places less importance on reproducing functional behaviour, or a top-down approach, which generally aim to reproduce the behaviour observed in real cognitive agents, but typically sacrifices adherence to constraints imposed by the neuro-biology. The focus of this thesis is Spaun, a large-scale brain model constructed using a combination of the bottom-up and top-down approaches to brain modelling. Spaun is currently the world’s largest functional brain model, capable of performing eight distinct cognitive tasks ranging from digit recognition to inductive reasoning. The thesis is organized to discuss three aspects of the Spaun model. First, it describes the original Spaun model, and explores how a top-down approach, known as the Semantic Pointer Architecture (SPA), has been combined with a bottom-up approach, known as the Neural Engineering Framework (NEF), to integrate six existing cognitive models into a unified cognitive model that is Spaun. Next, the thesis identifies some of the concerns with the original Spaun model, and show the modifications made to the network to remedy these issues. It also characterizes how the Spaun model was re-organized and re-implemented (to include the aforementioned modifications) as the Spaun 2.0 model. As part of the discussion of the Spaun 2.0 model, task performance results are presented that compare the original Spaun model and the re-implemented Spaun 2.0 model, demonstrating that the modifications to the Spaun 2.0 model have improved its accuracy on the working memory task, and the two induction tasks. Finally, three extensions to Spaun 2.0 are presented. These extensions take advantage of the re-organized Spaun model, giving Spaun 2.0 new capabilities – a motor system capable of adapting to unknown force fields applied to its arm; a visual system capable of processing 256×256 full-colour images; and the ability to follow general instructions. The Spaun model and architecture presented in this thesis demonstrate that by using the SPA and the NEF, it is not only possible to construct functional large-scale brain models, but to do so in a manner that supports complex extensions to the model. The final Spaun 2.0 model consists of approximately 6.6 million neurons, can perform 12 cognitive tasks, and has been demonstrated to reproduce behavioural and neurological data observed in natural cognitive agents.},
language = {en},
urldate = {2021-02-01},
school = {University of Waterloo (CA)},
author = {Choo, Feng-Xuan},
month = may,
year = {2018},
annote = {Extracted Annotations (3/7/2021, 3:58:00 PM)
"the SPA does not place limitations on how information is represented as semantic pointer, nor does it hypothesize the specic encoding schemata used in the biological brain; and, it should be emphasized that the encoding used in the example above is merely one of many possible ways the symbolic representation of the SPA can be used to represent information" (Choo 2018:47)
"each element of the vector is chosen from a normal distribution with a mean of 0 and a variance of 1=d, where d is the dimensionality of the vector." (Choo 2018:51)
Assuming x and y are unit vectors (if not, the equation can be normalized dividing by{\textbar}{\textbar}x{\textbar}{\textbar} {\textbar}{\textbar}y{\textbar}{\textbar}) (note on p.52)
"taking the reciprocal of small Fourier coecients results in large Fourier coecients (potentially innite) in the inverse semantic pointer" (Choo 2018:56)
"In the HRR, the approximate inverse of a vector is computed as in Equation (2.19), with the exception that instead of using the complex reciprocal, the complex" (Choo 2018:56)
"For a complex number (a + bi), the complex reciprocal is ( a2 b2 i). a +b a +b" (Choo 2018:56)
"conjugate is used.5" (Choo 2018:57)
"For a complex number (a + bi), the complex conjugate is (a bi). In essence, the complex conjugate is the complex reciprocal without compensating for the magnitude of the complex number." (Choo 2018:57)
"{\textbackslash}unitary vectors", and they have the crucial property that all of their Fourier coecients always have a magnitude6 of 1" (Choo 2018:58)
"A unitary semantic pointer is always of unit length (its vector magnitude is always 1)" (Choo 2018:58)
"Since the complex reciprocal and complex conjugate of a unit length complex number are equal, it follows that the inverse and approximate inverse of a unitary semantic pointer are also equal." (Choo 2018:59)
"The result of binding a unitary semantic pointer with another unitary semantic pointer is always a unitary semantic pointer." (Choo 2018:59)},
file = {Choo_2018_Spaun_2.pdf:files/5781/Choo_2018_Spaun_2.pdf:application/pdf},
}
@article{horst_completeness_2005,
series = {Selected {Papers} from the {International} {Semantic} {Web} {Conference}, 2004},
title = {Completeness, {Decidability} and {Complexity} of {Entailment} for {RDFSchema} and a {Semantic} {Extension} {Involving} the {OWL} {Vocabulary}},
volume = {3},
issn = {15708268},
url = {https://papers.ssrn.com/abstract=3199251},
doi = {10.1016/j.websem.2005.06.001},
abstract = {We prove that entailment for RDFS (RDF Schema) is decidable, NP-complete, and in P if the target graph does not contain blank nodes.We show that the standard set of entailment rules for RDFS is incomplete and that this can be corrected by allowing blank nodes in predicate position. We define semantic extensions of RDFS that involve datatypes and a subset of the OWL vocabulary that includes the property-related vocabulary (e.g. Functional- Property), the comparisons (e.g. sameAs and differentFrom) and the value restrictions (e.g. allValuesFrom). These semantic extensions are in line with the 'if-semantics' of RDFS and weaker than the 'iff-semantics' of D-entailment and OWL (DL or Full). For these semantic extensions we present entailment rules, prove completeness results, prove that consistency is in P and that, just as for RDFS, entailment is NP-complete, and in P if the target graph does not contain blank nodes. There are no restrictions on use to obtain decidability: classes can be used as instances.},
language = {en},
number = {2-3},
urldate = {2021-03-07},
journal = {Journal of Web Semantics},
author = {Horst, Herman J. ter},
year = {2005},
doi = {10.2139/ssrn.3199251},
keywords = {Semantics, Ontology, Completeness, Computational complexity, Entailment, completeness, entailment, ontology, semantics},
pages = {79--115},
file = {Horst_2005_Completeness,_Decidability_and_Complexity_of_Entailment_for_RDFSchema_and_a.pdf:files/5818/Horst_2005_Completeness,_Decidability_and_Complexity_of_Entailment_for_RDFSchema_and_a.pdf:application/pdf;Snapshot:files/5817/papers.html:text/html},
}
@article{doya_multiple_2002,
title = {Multiple {Model}-{Based} {Reinforcement} {Learning}},
volume = {14},
issn = {0899-7667, 1530-888X},
url = {https://www.mitpressjournals.org/doi/abs/10.1162/089976602753712972},
doi = {10.1162/089976602753712972},
abstract = {We propose a modular reinforcement learning architecture for nonlinear, nonstationary control tasks, which we call multiple model-based reinforcement learning (MMRL). The basic idea is to decompose a complex task into multiple domains in space and time based on the predictability of the environmental dynamics. The system is composed of multiple modules, each of which consists of a state prediction model and a reinforcement learning controller. The “responsibility signal,” which is given by the softmax function of the prediction errors, is used to weight the outputs of multiple modules, as well as to gate the learning of the prediction models and the reinforcement learning controllers. We formulate MMRL for both discrete-time, finite-state case and continuous-time, continuous-state case. The performance of MMRL was demonstrated for discrete case in a nonstationary hunting task in a grid world and for continuous case in a nonlinear, nonstationary control task of swinging up a pendulum with variable physical parameters.},
language = {en},
number = {6},
urldate = {2020-11-06},
journal = {Neural Computation},
author = {Doya, Kenji and Samejima, Kazuyuki and Katagiri, Ken-ichi and Kawato, Mitsuo},
month = jun,
year = {2002},
note = {Number: 6},
pages = {1347--1369},
file = {Doya_et_al_2002_Multiple_Model-Based_Reinforcement_Learning.pdf:files/5848/Doya_et_al_2002_Multiple_Model-Based_Reinforcement_Learning.pdf:application/pdf;mmbrl.png:files/5849/mmbrl.png:image/png},
}
@techreport{momennejad_predicting_2018,
type = {preprint},
title = {Predicting the {Future} with {Multi}-scale {Successor} {Representations}},
url = {http://biorxiv.org/lookup/doi/10.1101/449470},
abstract = {The successor representation (SR) is a candidate principle for generalization in reinforcement learning, computational accounts of memory, and the structure of neural representations in the hippocampus. Given a sequence of states, the SR learns a predictive representation for every given state that encodes how often, on average, each upcoming state is expected to be visited, even if it is multiple steps ahead. A discount or scale parameter determines how many steps into the future SR’s generalizations reach, enabling rapid value computation, subgoal discovery, and flexible decision-making in large trees. However, SR with a single scale could discard information for predicting both the sequential order of and the distance between states, which are common problems in navigation for animals and artificial agents. Here we propose a solution: an ensemble of SRs with multiple scales. We show that the derivative of multi-scale SR can reconstruct both the sequence of expected future states and estimate distance to goal. This derivative can be computed linearly: we show that a multi-scale SR ensemble is the Laplace transform of future states, and the inverse of this Laplace transform is a biologically plausible linear estimation of the derivative. Multi-scale SR and its derivative could lead to a common principle for how the medial temporal lobe supports both map-based and vector-based navigation.},
language = {en},
urldate = {2020-12-08},
institution = {Neuroscience},
author = {Momennejad, Ida and Howard, Marc W.},
month = oct,
year = {2018},
doi = {10.1101/449470},
file = {Momennejad_Howard_2018_Predicting_the_Future_with_Multi-scale_Successor_Representations.pdf:files/5838/Momennejad_Howard_2018_Predicting_the_Future_with_Multi-scale_Successor_Representations.pdf:application/pdf},
}
@article{colin_hierarchical_2016,
title = {Hierarchical reinforcement learning as creative problem solving},
volume = {86},
issn = {09218890},
url = {https://linkinghub.elsevier.com/retrieve/pii/S0921889016305371},
doi = {10.1016/j.robot.2016.08.021},
abstract = {Although creativity is studied from philosophy to cognitive robotics, a definition has proven elusive. We argue for emphasizing the creative process (the cognition of the creative agent), rather than the creative product (the artifact or behavior). Owing to developments in experimental psychology, the process approach has become an increasingly attractive way of characterizing creative problem solving. In particular, the phenomenon of insight, in which an individual arrives at a solution through a sudden change in perspective, is a crucial component of the process of creativity.},
language = {en},
urldate = {2020-11-03},
journal = {Robotics and Autonomous Systems},
author = {Colin, Thomas R. and Belpaeme, Tony and Cangelosi, Angelo and Hemion, Nikolas},
month = dec,
year = {2016},
keywords = {Robotics, Creativity, Insight, Hierarchical reinforcement learning},
pages = {196--206},
file = {Colin_et_al_2016_Hierarchical_reinforcement_learning_as_creative_problem_solving.pdf:files/5853/Colin_et_al_2016_Hierarchical_reinforcement_learning_as_creative_problem_solving.pdf:application/pdf},
}
@article{newell_reasoning_1979,
title = {Reasoning, problem solving and decision processes: the problem space as a fundamental category},
language = {en},
author = {Newell, Allen},
month = jun,
year = {1979},
pages = {31},
file = {Newell_1979_Reasoning,_problem_solving_and_decision_processes.pdf:files/5682/Newell_1979_Reasoning,_problem_solving_and_decision_processes.pdf:application/pdf},
}
@article{zilli_modeling_2008,
title = {Modeling the role of working memory and episodic memory in behavioral tasks},
volume = {18},
issn = {1098-1063},
doi = {10.1002/hipo.20382},
abstract = {The mechanisms of goal-directed behavior have been studied using reinforcement learning theory, but these theoretical techniques have not often been used to address the role of memory systems in performing behavioral tasks. This work addresses this shortcoming by providing a way in which working memory (WM) and episodic memory may be included in the reinforcement learning framework, then simulating the successful acquisition and performance of six behavioral tasks, drawn from or inspired by the rat experimental literature, that require WM or episodic memory for correct performance. With no delay imposed during the tasks, simulations with WM can solve all of the tasks at above the chance level. When a delay is imposed, simulations with both episodic memory and WM can solve all of the tasks except a disambiguation of odor sequences task.},
language = {en},
number = {2},
journal = {Hippocampus},
author = {Zilli, Eric A. and Hasselmo, Michael E.},
year = {2008},
pmid = {17979198},
pmcid = {PMC2376903},
keywords = {Animals, Rats, Models, Computer Simulation, Hippocampus, Maze Learning, Memory, Mental Recall, Neurological, Odorants, Reward, Short-Term, Space Perception, Memory, Short-Term, Models, Neurological},
pages = {193--209},
annote = {NOTES
Intro
1) Limitation: Markov property
={\textgreater} the optimal action to take in a particular observed state must depend only on that state and not on the recent history of the agent
Workaround: order-n Markov chains, ie an agent’s state = the set of its n most recent observations (or only the most relevant of them)
But still a finite number
2) WM vs EM
Working memory: ‘‘active and relevant only for a short period of time’’
Episodic memory: longer lasting memory that allows one to recall and re-experience personal events
Implementation in RL: memory part of the environment
={\textgreater} the agent can act upon it
\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_
Methods
Notations
table of values V, V(s) = expected discounted reward following state s
table of actions Q, Q(s,a) = value of taking action a in state s
SL sensory states
motor actions N/S/E/W change SL
Working memory
WM = the ability to maintain a representation of a stimulus online and to be able to manipulate it mentally
+1 action "add current sensory state to buffer"
+1 state for empty WM
Episodic memory
EM:
- addressable content
= can be elicited from a cue that is contained as part of the memory
- temporally indexed
= one can ‘‘replay’’ the memory from a retrieved point ( =/= semantic memory)
SEQ: sequence of n most recent states
+ 2 actions:
cue retrieval (Sep {\textless}- SL)
advance retrieval (Sep {\textless}- next state in SEQ)
+ 1 state for empty EM "nothing recalled"
WM can buffer episodic retrieval
Rewards and Limitations on Actions
- for actions that don't change the agent’s state or moving backwards: reward R = -1. Includes
- attempting to move out of the environment or into a barrier
- store something in WM that is already stored
- to advance episodic retrieval without first cuing retrieval
- moving backward
Most tasks:
- correct move: R = +9.5
- incorrect move: R = -6
- other actions: R = +0.05
limit of 100 on the number of steps
Odor sequence disambiguation:
- correct move: R = +1
- incorrect move: R = -5
- other actions: R = +0.05
\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_
Results
Task 1: Spatial Sequence Disambiguation (SSD)
I-shape maze
start from the bottom of an arm, end up in the opposite top arm
repositioned at a random start bottom arm for the next trial
delayed task: clear WM when repositioning
both the episodic and WM agents were able to solve the nondelayed task, whereas only the episodic agent could solve the delayed version
the standard agent could not learn the task in either version
Task 2: Spatial Alternation
M-shaped maze
begin at the bottom of the center hallway in the maze and proceed up to the choice point.
First trial:
- turn either left or right and received a positive reward at the end of the arm
- continue along a return arm and back to the starting point
- proceed again up the center hallway to the choice point (at the starting point, the agent was prevented from entering the side hallway instead of the center hallwayby use of a barrier).
After the first trial:
positive reward if opposite direction as on the previous trial,negative otherwise
Delayed version: WM cleared on every visit to the start position (bottom of the stem)
Same result as before: WM and WM+EP work for nondelayed, WM+EP for delayed
Task 3: Nonmatch to Position
same principle, same results
Task 4: Nonmatch to Sample
- sample stage in which only one of the two levers was available for making a response, - then a choice stage in which both levers were available.
Negative reward if actioning the same lever (as available during the sample), positive reward for the other lever
After making a response at a lever, the animal was moved back to the starting position
WM cleared before the sample stage
Delayed version: WM also cleared before the choice stage
In principle, both versions of this task were solvable using EM; however, the nondelayed version was more readily solved using only WM
Task 5: Odor Sequence Disambiguation
linear track with five pairs of odors
On each trial, select one odor of each pair.
Positive reward if right odor, negative otherwise
Correction before advancing to the next pair, except for the final pair
Delayed version: WM cleared before the final pair
Same results as task 4:
WM performs better for nondelayed task
WM only cannot solve delayed task
the simulation was not run long enough to show the agents with EM learning to correctly perform the task
Task 6: Tone-Cued Spatial Alternation
same as task 2 with sounds
each time a tone is presented, the agent has to make the opposite response as on the previous presentation (2 independant tones)
={\textgreater} best use-case for EM (remember the sound: cue retrieval)
non-delayed task: WM can use a simple alernation strategy
both tasks: EM performs better
\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_
Discussion
WM: if a task can be solved based on which of a set of states was most recently experienced
EM: if a task can be solved based on the states that previously followed some given experienced state on the current trial
},
file = {Zilli_Hasselmo_2008_Modeling_the_role_of_working_memory_and_episodic_memory_in_behavioral_tasks.pdf:files/5822/Zilli_Hasselmo_2008_Modeling_the_role_of_working_memory_and_episodic_memory_in_behavioral_tasks.pdf:application/pdf},
}
@article{botvinick_reinforcement_2019,
title = {Reinforcement {Learning}, {Fast} and {Slow}},
volume = {23},
issn = {13646613},
url = {https://linkinghub.elsevier.com/retrieve/pii/S1364661319300610},
doi = {10.1016/j.tics.2019.02.006},
language = {en},
number = {5},
urldate = {2020-10-01},
journal = {Trends in Cognitive Sciences},
author = {Botvinick, Matthew and Ritter, Sam and Wang, Jane X. and Kurth-Nelson, Zeb and Blundell, Charles and Hassabis, Demis},
month = may,
year = {2019},
pages = {408--422},
annote = {Extracted Annotations (3/7/2021, 3:57:27 PM)
"two key deep RL methods that mitigate the sample efficiency problem: episodic deep RL and meta-RL" (Botvinick, et and al 2019:409)
"incremental parameter adjustment" (Botvinick, et and al 2019:409)
"weak inductive bias" (Botvinick, et and al 2019:410)},
file = {Botvinick_et_al_2019_Reinforcement_Learning,_Fast_and_Slow.pdf:files/5847/Botvinick_et_al_2019_Reinforcement_Learning,_Fast_and_Slow.pdf:application/pdf},
}
@article{co-reyes_guiding_2019,
title = {Guiding policies with language via meta-learning},
abstract = {Behavioral skills or policies for autonomous agents are conventionally learned from reward functions, via reinforcement learning, or from demonstrations, via imitation learning. However, both modes of task specification have their disadvantages: reward functions require manual engineering, while demonstrations require a human expert to be able to actually perform the task in order to generate the demonstration. Instruction following from natural language instructions provides an appealing alternative: in the same way that we can specify goals to other humans simply by speaking or writing, we would like to be able to specify tasks for our machines. However, a single instruction may be insufficient to fully communicate our intent or, even if it is, may be insufficient for an autonomous agent to actually understand how to perform the desired task. In this work, we propose an interactive formulation of the task specification problem, where iterative language corrections are provided to an autonomous agent, guiding it in acquiring the desired skill. Our proposed language-guided policy learning algorithm can integrate an instruction and a sequence of corrections to acquire new skills very quickly. In our experiments, we show that this method can enable a policy to follow instructions and corrections for simulated navigation and manipulation tasks, substantially outperforming direct, non-interactive instruction following.},
language = {en},
author = {Co-Reyes, John D},
year = {2019},
pages = {17},
annote = {Extracted Annotations (3/7/2021, 3:58:01 PM)
"language instruction" (Co-Reyes 2019:19)
"language correction" (Co-Reyes 2019:19)
"meta-trained to understand both instructions and corrections properly" (Co-Reyes 2019:21)
"put them in the context of its own previous trajectories, and associate them with objects and events in the world" (Co-Reyes 2019:21)},
file = {Co-Reyes_2019_Guiding_policies_with_language_via_meta-learning.pdf:files/5854/Co-Reyes_2019_Guiding_policies_with_language_via_meta-learning.pdf:application/pdf},
}
@article{kwisthout_relevancy_2012,
title = {Relevancy in {Problem} {Solving}: {A} {Computational} {Framework}},
volume = {5},
issn = {1932-6246},
shorttitle = {Relevancy in {Problem} {Solving}},
url = {https://docs.lib.purdue.edu/jps/vol5/iss1/4},
doi = {10.7771/1932-6246.1141},
abstract = {When computer scientists discuss the computational complexity of, for example, finding the shortest path from building A to building B in some town or city, their starting point typically is a formal description of the problem at hand, e.g., a graph with weights on every edge where buildings correspond to vertices, routes between buildings to edges, and route-distances to edge-weights. Given such a formal description, either tractability or intractability of the problem is established, by proving that the problem either enjoys a polynomial time algorithm or is NP-hard. However, this problem description is in fact an abstraction of the actual problem of being in A and desiring to go to B: it focuses on the relevant aspects of the problem (e.g., distances between landmarks and crossings) and leaves out a lot of irrelevant details.},
language = {en},
number = {1},
urldate = {2020-12-06},
journal = {The Journal of Problem Solving},
author = {Kwisthout, Johan},
month = oct,
year = {2012},
file = {Kwisthout_2012_Relevancy_in_Problem_Solving.pdf:files/5842/Kwisthout_2012_Relevancy_in_Problem_Solving.pdf:application/pdf},
}
@inproceedings{goudyme_intention_2019,
address = {Toulouse, France},
title = {Intention et logique épistémique dynamique},
url = {https://hal.archives-ouvertes.fr/hal-02161427},
urldate = {2021-03-07},
booktitle = {Rencontres des {Jeunes} {Chercheurs} en {Intelligence} {Artificielle} ({RJCIA} 2019)},
author = {Goudyme, Alix and Chetcuti-Sperandio, Nathalie and Lagrue, Sylvain and De Lima, Tiago},
month = jul,
year = {2019},
keywords = {Dynamic epistemic logic, epistemic games, intention, jeux épistemiques, Logique épistémique dynamique},
pages = {1--9},
annote = {Co-localisées avec la Plate-Forme Intelligence Artificielle (PFIA 2019)},
file = {Goudyme_et_al_2019_Intention_et_logique_epistemique_dynamique.pdf:files/5819/Goudyme_et_al_2019_Intention_et_logique_epistemique_dynamique.pdf:application/pdf},
}
@inproceedings{wang_ontology-based_2016,
address = {Cham},
series = {Lecture {Notes} in {Computer} {Science}},
title = {Ontology-{Based} {Deep} {Restricted} {Boltzmann} {Machine}},
volume = {9827},
isbn = {978-3-319-44402-4 978-3-319-44403-1},
url = {http://link.springer.com/10.1007/978-3-319-44403-1_27},
doi = {10.1007/978-3-319-44403-1_27},
abstract = {Deep neural networks are known for their capabilities for automatic feature learning from data. For this reason, previous research has tended to interpret deep learning techniques as data-driven methods, while few advances have been made from knowledge-driven perspectives. We propose to design a semantic rich deep learning model from a knowledge driven perspective, by introducing formal semantics into deep learning process. We propose ontology-based deep restricted Boltzmann machine (OB-DRBM), in which we use ontology to guide architecture design of deep restricted Boltzmann machines (DRBM), as well as to assist in their training and validation processes. Our model learns a set of related semantic-rich data representations from both formal semantics and data distribution. Representations in this set correspond to concepts at various semantic levels in a domain ontology. We show that our model leads to an improved performance, when compared with conventional deep learning models in classification tasks.},
language = {en},
urldate = {2021-02-02},
booktitle = {Database and {Expert} {Systems} {Applications}},
publisher = {Springer International Publishing},
author = {Wang, Hao and Dou, Dejing and Lowd, Daniel},
editor = {Hartmann, Sven and Ma, Hui},
year = {2016},
keywords = {Convolutional Neural Network, Deep Learning, Domain Ontology, Formal Semantic, Sentiment Analysis},
pages = {431--445},
annote = {Series Title: Lecture Notes in Computer Science},
file = {Wang_et_al_2016_Ontology-Based_Deep_Restricted_Boltzmann_Machine.pdf:files/5820/Wang_et_al_2016_Ontology-Based_Deep_Restricted_Boltzmann_Machine.pdf:application/pdf},
}
@article{pal_review_2020,
title = {A {Review} of {Platforms} for the {Development} of {Agent} {Systems}},
url = {http://arxiv.org/abs/2007.08961},
abstract = {Agent-based computing is an active field of research with the goal of building autonomous software of hardware entities. This task is often facilitated by the use of dedicated, specialized frameworks. For almost thirty years, many such agent platforms have been developed. Meanwhile, some of them have been abandoned, others continue their development and new platforms are released. This paper presents a up-to-date review of the existing agent platforms and also a historical perspective of this domain. It aims to serve as a reference point for people interested in developing agent systems. This work details the main characteristics of the included agent platforms, together with links to specific projects where they have been used. It distinguishes between the active platforms and those no longer under development or with unclear status. It also classifies the agent platforms as general purpose ones, free or commercial, and specialized ones, which can be used for particular types of applications.},
language = {en},
urldate = {2021-03-07},
journal = {arXiv:2007.08961 [cs]},
author = {Pal, Constantin-Valentin and Leon, Florin and Paprzycki, Marcin and Ganzha, Maria},
month = jul,
year = {2020},
note = {arXiv: 2007.08961},
keywords = {68T42, Computer Science - Multiagent Systems},
pages = {40},
annote = {Comment: 40 pages, 2 figures, 9 tables, 83 references},
file = {arXiv.org Snapshot:files/5693/2007.html:text/html;Pal_et_al_2020_A_Review_of_Platforms_for_the_Development_of_Agent_Systems.pdf:files/5694/Pal_et_al_2020_A_Review_of_Platforms_for_the_Development_of_Agent_Systems.pdf:application/pdf},
}
@inproceedings{neubert_learning_2017,
title = {Learning {Vector} {Symbolic} {Architectures} for {Reactive} {Robot} {Behaviours}},
url = {https://www.tu-chemnitz.de/etit/proaut/publications/IROS2016_neubert.pdf},
abstract = {Vector Symbolic Architectures (VSA) combine a hypervector space and a set of operations on these vectors. Hypervectors provide powerful and noise-robust representations and VSAs are associated with promising theoretical properties for approaching high-level cognitive tasks. However, a major drawback of VSAs is the lack of opportunities to learn them from training data. Their power is merely an effect of good (and elaborate) design rather than learning. We exploit highlevel knowledge about the structure of reactive robot problems to learn a VSA based on training data. We demonstrate preliminary results on a simple navigation task. Given a successful demonstration of a navigation run by pairs of sensor input and actuator output, the system learns a single hypervector that encodes this reactive behaviour. When executing (and combining) such VSA-based behaviours, the advantages of hypervectors (i.e. the representational power and robustness to noise) are preserved. Moreover, a particular beauty of this approach is that it can learn encodings for behaviours that have exactly the same form (a hypervector) no matter how complex the sensor input or the behaviours are.},
language = {en},
urldate = {2021-03-07},
booktitle = {Workshop on {Machine} {Learning} {Methods} for {High}-{Level} {Cognitive} {Capabilities} in {Robotics}},
author = {Neubert, Peer and Schubert, Stefan and Protzel, Peter},
year = {2017},
pages = {3},
file = {Neubert_et_al_2017_Learning_Vector_Symbolic_Architectures_for_Reactive_Robot_Behaviours.pdf:files/5683/Neubert_et_al_2017_Learning_Vector_Symbolic_Architectures_for_Reactive_Robot_Behaviours.pdf:application/pdf;Snapshot:files/5696/e85769cc66ebf637f1465356a33142af7c4818d9.html:text/html},
}
@article{stewart_neural_2011,
title = {Neural {Cognitive} {Modelling}: {A} {Biologically} {Constrained} {Spiking} {Neuron} {Model} of the {Tower} of {Hanoi} {Task}},
volume = {33},
issn = {1069-7977},
shorttitle = {Neural {Cognitive} {Modelling}},
url = {https://escholarship.org/uc/item/6kv930kg},
abstract = {Author(s): Stewart, Terrence; Eliasmith, Chris},
language = {en},
number = {33},
urldate = {2021-03-07},
journal = {Proceedings of the Annual Meeting of the Cognitive Science Society},
author = {Stewart, Terrence and Eliasmith, Chris},
year = {2011},
file = {Snapshot:files/5704/6kv930kg.html:text/html;Stewart_Eliasmith_2011_Neural_Cognitive_Modelling.pdf:files/5705/Stewart_Eliasmith_2011_Neural_Cognitive_Modelling.pdf:application/pdf},
}
@inproceedings{petrucci_ontology_2016,
address = {Cham},
series = {Lecture {Notes} in {Computer} {Science}},
title = {Ontology {Learning} in the {Deep}},
isbn = {978-3-319-49004-5},
doi = {10.1007/978-3-319-49004-5_31},
abstract = {Recent developments in the area of deep learning have been proved extremely beneficial for several natural language processing tasks, such as sentiment analysis, question answering, and machine translation. In this paper we exploit such advances by tailoring the ontology learning problem as a transductive reasoning task that learns to convert knowledge from natural language to a logic-based specification. More precisely, using a sample of definitory sentences generated starting by a synthetic grammar, we trained Recurrent Neural Network (RNN) based architectures to extract OWL formulae from text. In addition to the low feature engineering costs, our system shows good generalisation capabilities over the lexicon and the syntactic structure. The encouraging results obtained in the paper provide a first evidence of the potential of deep learning techniques towards long term ontology learning challenges such as improving domain independence, reducing engineering costs, and dealing with variable language forms.},
language = {en},
booktitle = {Knowledge {Engineering} and {Knowledge} {Management}},
publisher = {Springer International Publishing},
author = {Petrucci, Giulio and Ghidini, Chiara and Rospocher, Marco},
editor = {Blomqvist, Eva and Ciancarini, Paolo and Poggi, Francesco and Vitali, Fabio},
year = {2016},
keywords = {Cardinality Restriction, Function Word, Ontology Learning, Recurrent Neural Network, Statistical Machine Translation},
pages = {480--495},
}
@inproceedings{hilario_modular_1994,
title = {Modular {Integration} of {Connectionist} and {Symbolic} {Processing} in {Knowledge}-{Based} {Systems}},
abstract = {: MIX is an ESPRIT project aimed at developing strategies and tools for integrating symbolic and neural methods in hybrid systems. The project arose from the observation that current hybrid systems are generally small-scale experimental systems which couple one symbolic and one connectionist model, often in an ad hoc fashion. Hence the objective of building a versatile testbed for the design, prototyping and assessment of a variety of hybrid models or architectures, in particular those which combine diverse neural network models with rule/model-based, cased-based, and fuzzy reasoning. A multiagent approach has been chosen to facilitate modular implementation of these hybrid models, which will be tested in the context of real-world applications in the steel and automobile industries. 1. Introduction Current efforts at integrating symbolic and neural processing can be divided into two major approaches. In the unified approach, better known as connectionist symbol processing, neural netw...},
language = {en},
booktitle = {In {Proceedings} of the {International} {Symposium} on {Integrating} {Knowledge} and {Neural} {Heuristics}},
publisher = {Morgan-Kaufmann},
author = {Hilario, Mélanie and Pellegrini, Christian and Alexandre, Frédéric},
year = {1994},
pages = {123--132},
file = {Citeseer - Snapshot:files/5709/summary.html:text/html;Hilario_et_al_1994_Modular_Integration_of_Connectionist_and_Symbolic_Processing_in_Knowledge-Based.pdf:files/5710/Hilario_et_al_1994_Modular_Integration_of_Connectionist_and_Symbolic_Processing_in_Knowledge-Based.pdf:application/pdf},
}
@inproceedings{eidoon_ontology_2008,
address = {Berlin, Heidelberg},
series = {Lecture {Notes} in {Computer} {Science}},
title = {Ontology {Matching} {Using} {Vector} {Space}},
isbn = {978-3-540-78646-7},
doi = {10.1007/978-3-540-78646-7_45},
abstract = {Interoperability of heterogeneous systems on the Web will be achieved through an agreement between the underlying ontologies. Ontology matching is an operation that takes two ontologies and determines their semantic mapping. This paper presents a method of ontology matching which is based on modeling ontologies in a vector space and estimating their similarity degree by matching their concept vectors. The proposed method is successfully applied to the test suit of Ontology Alignment Evaluation Initiative 2005 [10] and compared to the results reported by other methods. In terms of precision and recall, the results look promising.},
language = {en},
booktitle = {Advances in {Information} {Retrieval}},
publisher = {Springer},
author = {Eidoon, Zahra and Yazdani, Nasser and Oroumchian, Farhad},
editor = {Macdonald, Craig and Ounis, Iadh and Plachouras, Vassilis and Ruthven, Ian and White, Ryen W.},
year = {2008},
keywords = {ontology matching, semantic web, vector space},
pages = {472--481},
file = {Eidoon_et_al_2008_Ontology_Matching_Using_Vector_Space.pdf:files/5746/Eidoon_et_al_2008_Ontology_Matching_Using_Vector_Space.pdf:application/pdf},
}
@inproceedings{choo_general_2013,
title = {General {Instruction} {Following} in a {Large}-{Scale} {Biologically} {Plausible} {Brain} {Model}},
abstract = {We present a spiking neuron brain model implemented in 318,870 LIF neurons organized with distinct cortical modules, a basal ganglia, and a thalamus, that is capable of flexibly following memorized commands. Neural activity represents a structured set of rules, such as "If you see a 1, then push button A, and if you see a 2, then push button B". Synaptic connections between these neurons and the basal ganglia, thalamus, and other areas cause the system to detect when rules should be applied and to then do so. The model gives a reaction time difference of 77 ms between the simple and two-choice reaction time tasks, and requires 384 ms per item for sub-vocal counting, consistent with human experimental results. This is the first biologically realistic spiking neuron model capable of flexibly responding to complex structured instructions.},
language = {en},
booktitle = {35th {Annual} {Conference} of the {Cognitive} {Science} {Society}},
publisher = {Cognitive Science Society},
author = {Choo, Xuan and Eliasmith, Chris},
year = {2013},
pages = {322--327},
file = {Choo_Eliasmith_2013_General_Instruction_Following_in_a_Large-Scale_Biologically_Plausible_Brain.pdf:files/5690/Choo_Eliasmith_2013_General_Instruction_Following_in_a_Large-Scale_Biologically_Plausible_Brain.pdf:application/pdf},
}
@article{brennan_new_2012,
title = {New frameworks for studying and assessing the development of computational thinking},
abstract = {Computational thinking is a phrase that has received considerable attention over the past several years – but there is little agreement about what computational thinking encompasses, and even less agreement about strategies for assessing the development of computational thinking in young people. We are interested in the ways that design-based learning activities – in particular, programming interactive media – support the development of computational thinking in young people. Over the past several years, we have developed a computational thinking framework that emerged from our studies of the activities of interactive media designers. Our context is Scratch – a programming environment that enables young people to create their own interactive stories, games, and simulations, and then share those creations in an online community with other young programmers from around the world.},
language = {en},
author = {Brennan, Karen and Resnick, Mitchel},
year = {2012},
pages = {25},
file = {Brennan_Resnick_2012_New_frameworks_for_studying_and_assessing_the_development_of_computational.pdf:files/5676/Brennan_Resnick_2012_New_frameworks_for_studying_and_assessing_the_development_of_computational.pdf:application/pdf},
}
@article{guggemos_predictors_2021,
title = {On the predictors of computational thinking and its growth at the high-school level},
volume = {161},
issn = {0360-1315},
url = {http://www.sciencedirect.com/science/article/pii/S036013152030258X},
doi = {10.1016/j.compedu.2020.104060},
abstract = {Computational thinking (CT) is a key 21st-century skill. This paper contributes to CT research by investigating CT predictors among upper secondary students in a longitudinal and natural classroom setting. The hypothesized predictors are grouped into three areas: student characteristics, home environment, and learning opportunities. CT is measured with the Computational Thinking Test (CTt), an established performance test. N = 202 high-school students, at three time points over one school year, act as the sample and latent growth curve modeling as the analysis method. CT self-concept, followed by reasoning skills and gender, show the strongest association with the level of CT. Computer literacy, followed by duration of computer use and formal learning opportunities during the school year, have the strongest association with CT growth. Variables from all three areas seem to be important for predicting either CT level or growth. An explained variance of 70.4\% for CT level and 61.2\% for CT growth might indicate a good trade-off between the comprehensiveness and parsimony of the conceptual framework. The findings contribute to a better understanding of CT as a construct and have implications for CT instruction, e.g., the role of computer science and motivation in CT learning.},
language = {en},
urldate = {2020-12-15},
journal = {Computers \& Education},
author = {Guggemos, Josef},
month = feb,
year = {2021},
keywords = {Computational thinking, Motivation, Gender and home environment, Longitudinal study, Reasoning skills},
pages = {104060},
file = {Guggemos_2021_On_the_predictors_of_computational_thinking_and_its_growth_at_the_high-school.pdf:files/5677/Guggemos_2021_On_the_predictors_of_computational_thinking_and_its_growth_at_the_high-school.pdf:application/pdf;ScienceDirect Snapshot:files/5678/S036013152030258X.html:text/html},
}
@inproceedings{atlan_apprentissage_2019,
title = {Apprentissage de la pensée informatique : de la formation des enseignant·e·s à la formation de tou·te·s les citoyen·ne·s},
shorttitle = {Apprentissage de la pensée informatique},
url = {https://hal.inria.fr/hal-02145480},
abstract = {En France au cours de ces dernières années, l'apprentissage de l'informatique (sous le terme d'« apprentissage du code ») est entré dans les programmes scolaires, en primaire et secondaire. Cet apprentissage vise notamment le développement de la pensée informatique (au sens défini par Wing) afin de permettre aux élèves, filles et garçons, d'acquérir les bases, une étape initiale vers la maîtrise du numérique, sous tous ses aspects (science, technologie, industrie et culture). Cependant, peu d'enseignant·e·s, ou de parents, ont été formé·e·s pour enseigner les sciences du numérique ou éduquer à leurs fondements et leurs usages. De plus, si le système éducatif avance progressivement au niveau de ces objectifs, dans la vie quotidienne et en contexte professionnel, il existe aussi un besoin de formation tout au long de la vie à la pensée informatique. Des projets d'envergure sur l'apprentissage du code sont aujourd'hui forts d'un véritable succès en matière de support à la formation des professionnel·le·s de l'éducation sur ces sujets. Cependant ces projets nécessitent une main d'oeuvre importante tant pour la création de ressources que pour leur actualisation, afin de rester en phase avec les besoins de formation dans un domaine en évolution constante. Dans le but de développer davantage les objectifs de démystification de la pensée informatique vers un large public de citoyens et de citoyennes, nous voulons questionner ici la manière dont il est possible de concevoir une initiative concrète et opérationnelle qui relève ce défi. Partageons ici une proposition et discutons-la. Ce qui est proposé porte un nom : une Université, Citoyenne en Sciences et Culture du Numérique (\#UCscN) qui s'inscrit dans la tradition des universités populaires. Il s'agit donc très simplement d'étendre à toutes et tous cette éducation pour penser l'informatique en capitalisant sur l'expérience acquise de Class'Code en formant les professionnel·le·s de l'éducation.},
language = {fr},
urldate = {2021-03-07},
author = {Atlan, Corinne and Archambault, Jean-Pierre and Banus, Olivier and Bardeau, Frédéric and Blandeau, Amélie and Cois, Antonin and Courbin-Coulaud, Martine and Giraudon, Gérard and Lefèvre, Saint-Clair and Letard, Valérie and Masse, Bastien and Masseglia, Florent and Ninassi, Benjamin and Quatrebarbes, Sophie de and Romero, Margarida and Roy, Didier and Viéville, Thierry},
month = jun,
year = {2019},
file = {Atlan_et_al_2019_Apprentissage_de_la_pensee_informatique.pdf:files/5712/Atlan_et_al_2019_Apprentissage_de_la_pensee_informatique.pdf:application/pdf;Snapshot:files/5711/hal-02145480.html:text/html},
}
@inproceedings{romero_analyse_2018,
title = {Analyse comparative d’une activité d’apprentissage de la programmation en mode branché et débranché},
url = {https://hal.inria.fr/hal-01861732},
abstract = {L’introduction de la programmation à l’école peut être un levier pour développer la pensée informatique en lien avec une démarche de résolution de problèmes. Dans ce contexte, nous nous intéressons aux différents types d’activités d’apprentissage de la programmation dans le but d’établir un protocole pour comparer les activités branchées et débranchées à l’école, et plus particulièrement de voir dans quelle mesure une activité débranchée permet un transfert de compétences vers l’apprentissage de la programmation. Nous discutons la méthodologie et les résultats en lien aux observations réalisées au cours des activités de formation Class’Code.},
language = {fr},
urldate = {2021-03-07},
author = {Romero, Margarida and Lille, Benjamin and Viéville, Thierry and Duflot-Kremer, Marie and Smet, Cindy de and Belhassein, David},
month = aug,
year = {2018},
pages = {11},
file = {Romero_et_al_2018_Analyse_comparative_d’une_activite_d’apprentissage_de_la_programmation_en_mode.pdf:files/5700/Romero_et_al_2018_Analyse_comparative_d’une_activite_d’apprentissage_de_la_programmation_en_mode.pdf:application/pdf;Snapshot:files/5699/hal-01861732.html:text/html},
}
@article{romero_computational_2017,
title = {Computational thinking development through creative programming in higher education},
volume = {14},
copyright = {2017 The Author(s)},
issn = {2365-9440},
url = {https://educationaltechnologyjournal.springeropen.com/articles/10.1186/s41239-017-0080-z},
doi = {10.1186/s41239-017-0080-z},
abstract = {Creative and problem-solving competencies are part of the so-called twenty-first century skills. The creative use of digital technologies to solve problems is also related to computational thinking as a set of cognitive and metacognitive strategies in which the learner is engaged in an active design and creation process and mobilized computational concepts and methods. At different educational levels, computational thinking can be developed and assessed through solving ill-defined problems. This paper introduces computational thinking in the context of Higher Education creative programming activities. In this study, we engage undergraduate students in a creative programming activity using Scratch. Then, we analyze the computational thinking scores of an automatic analysis tool and the human assessment of the creative programming projects. Results suggested the need for a human assessment of creative programming while pointing the limits of an automated analytical tool, which does not reflect the creative diversity of the Scratch projects and overrates algorithmic complexity.},
language = {en},
number = {1},
urldate = {2021-03-07},
journal = {International Journal of Educational Technology in Higher Education},
author = {Romero, Margarida and Lepage, Alexandre and Lille, Benjamin},
month = dec,
year = {2017},
note = {Number: 1
Publisher: SpringerOpen},
pages = {1--15},
file = {Romero_et_al_2017_Computational_thinking_development_through_creative_programming_in_higher.pdf:files/5726/Romero_et_al_2017_Computational_thinking_development_through_creative_programming_in_higher.pdf:application/pdf;Snapshot:files/5725/s41239-017-0080-z.html:text/html},
}
@phdthesis{lodi_introducing_2020,
type = {phdthesis},
title = {Introducing {Computational} {Thinking} in {K}-12 {Education}: {Historical}, {Epistemological}, {Pedagogical}, {Cognitive}, and {Affective} {Aspects}},
shorttitle = {Introducing {Computational} {Thinking} in {K}-12 {Education}},
url = {https://hal.inria.fr/tel-02981951},
abstract = {Introduction of scientific and cultural aspects of Computer Science (CS) (called "Computational Thinking" - CT) in K-12 education is fundamental. We focus on three crucial areas. 1. Historical, philosophical, and pedagogical aspects. What are the big ideas of CS we must teach? What are the historical and pedagogical contexts in which CT emerged, and why are relevant? What is the relationship between learning theories (e.g., constructivism) and teaching approaches (e.g., plugged and unplugged)? 2. Cognitive aspects. What is the sentiment of generalist teachers not trained to teach CS? What misconceptions do they hold about concepts like CT and "coding"? 3. Affective and motivational aspects. What is the impact of personal beliefs about intelligence (mindset) and about CS ability? What the role of teaching approaches? This research has been conducted both through historical and philosophical argumentation, and through quantitative and qualitative studies (both on nationwide samples and small significant ones), in particular through the lens of (often exaggerated) claims about transfer from CS to other skills. Four important claims are substantiated. 1. CS should be introduced in K-12 as a tool to understand and act in our digital world, and to use the power of computation for meaningful learning. CT is the conceptual sediment of that learning. We designed a curriculum proposal in this direction. 2. The expressions CT (useful to distantiate from digital literacy) and "coding" can cause misconceptions among teachers, who focus mainly on transfer to general thinking skills. Both disciplinary and pedagogical teacher training is hence needed. 3. Some plugged and unplugged teaching tools have intrinsic constructivist characteristics that can facilitate CS learning, as shown with proposed activities. 4. Growth mindset is not automatically fostered by CS, while not studying CS can foster fixed beliefs. Growth mindset can be fostered by creative computing, leveraging on its constructivist aspects.},
language = {en},
urldate = {2021-03-07},
school = {Dipartimento di Informatica - Scienza e Ingegneria, Alma Mater Studiorum - Università di Bologna},
author = {Lodi, Michael},
month = apr,
year = {2020},
keywords = {coding, computing education, constructivism, Computational thinking, computer science education, K-12 education, constructionism, CS mindset, growth mindset, higher-order thinking skills., implicit theories, informatics education, misconceptions, Papert, pensée informatique, self-theories, transfer, Wing},
file = {Lodi_2020_Introducing_Computational_Thinking_in_K-12_Education.pdf:files/5733/Lodi_2020_Introducing_Computational_Thinking_in_K-12_Education.pdf:application/pdf;Snapshot:files/5732/tel-02981951.html:text/html},
}
@article{simon_modeling_1976,
title = {Modeling strategy shifts in a problem-solving task},
volume = {8},
issn = {1095-5623(Electronic),0010-0285(Print)},
url = {http://www.sciencedirect.com/science/article/pii/0010028576900050},
doi = {10.1016/0010-0285(76)90005-0},
abstract = {Fitted a computer simulation model to human laboratory data for the Missionaries and Cannibals task to explain (a) the effects upon problem performance of giving a hint and (b) the effects of solving the problem a 2nd time after 1 successful solution had been achieved. Two experiments were conducted. Most of the variance in the relative frequencies of different moves can be explained by positing that the effect of the hint, or of previous experience in solving the problem, is to cause Ss to switch more promptly from a strategy of balancing the numbers of missionaries and cannibals on both sides of the river, to a means-ends strategy. (PsycInfo Database Record (c) 2020 APA, all rights reserved)},
language = {en},
number = {1},
journal = {Cognitive Psychology},
author = {Simon, Herbert A. and Reed, Stephen K.},
year = {1976},
note = {Publisher: Academic Press},
keywords = {Cues, Problem Solving, Strategies},
pages = {86--97},
file = {Simon_Reed_1976_Modeling_strategy_shifts_in_a_problem-solving_task.pdf:files/5679/Simon_Reed_1976_Modeling_strategy_shifts_in_a_problem-solving_task.pdf:application/pdf;Snapshot:files/5691/0010028576900050.html:text/html},
}
@inproceedings{alexandre_creativity_2020,
title = {Creativity explained by {Computational} {Cognitive} {Neuroscience}},
url = {https://hal.inria.fr/hal-02891491},
abstract = {Recently, models in Computational Cognitive Neuro-science (CCN) have gained a renewed interest because they could help analyze current limitations in Artificial Intelligence (AI) and propose operational ways to address them. These limitations are related to difficulties in giving a semantic grounding to manipulated concepts , in coping with high dimensionality and in managing uncertainty. In this paper, we describe the main principles and mechanisms of these models and explain that they can be directly transferred to Computational Creativity (CC), to propose operational mechanisms but also a better understanding of what creativity is.},
language = {en},
urldate = {2021-03-07},
booktitle = {{ICCC}'20 - {International} {Conference} on {Computational} {Creativity}},
author = {Alexandre, Frédéric},
month = sep,
year = {2020},
pages = {4},
file = {Alexandre_2020_Creativity_explained_by_Computational_Cognitive_Neuroscience.pdf:files/5714/Alexandre_2020_Creativity_explained_by_Computational_Cognitive_Neuroscience.pdf:application/pdf;Snapshot:files/5713/hal-02891491.html:text/html},
}
@article{ribeiro_embedding_1998,
title = {Embedding a {Priori} {Knowledge} in {Reinforcement} {Learning}},
volume = {21},
issn = {1573-0409},
url = {https://doi.org/10.1023/A:1007968115863},
doi = {10.1023/A:1007968115863},
abstract = {In the last years, temporal differences methods have been put forward as convenient tools for reinforcement learning. Techniques based on temporal differences, however, suffer from a serious drawback: as stochastic adaptive algorithms, they may need extensive exploration of the state-action space before convergence is achieved. Although the basic methods are now reasonably well understood, it is precisely the structural simplicity of the reinforcement learning principle – learning through experimentation – that causes these excessive demands on the learning agent. Additionally, one must consider that the agent is very rarely a tabula rasa: some rough knowledge about characteristics of the surrounding environment is often available. In this paper, I present methods for embedding a priori knowledge in a reinforcement learning technique in such a way that both the mathematical structure of the basic learning algorithm and the capacity to generalise experience across the state-action space are kept. Extensive experimental results show that the resulting variants may lead to good performance, provided a sensible balance between risky use of prior imprecise knowledge and cautious use of learning experience is adopted.},
language = {en},
number = {1},
urldate = {2021-03-07},
journal = {Journal of Intelligent and Robotic Systems},
author = {Ribeiro, Carlos H. C.},
month = jan,
year = {1998},
pages = {51--71},
file = {Ribeiro_1998_Embedding_a_Priori_Knowledge_in_Reinforcement_Learning.pdf:files/5692/Ribeiro_1998_Embedding_a_Priori_Knowledge_in_Reinforcement_Learning.pdf:application/pdf},
}
@article{gosmann_vector-derived_2019,
title = {Vector-{Derived} {Transformation} {Binding}: {An} {Improved} {Binding} {Operation} for {Deep} {Symbol}-{Like} {Processing} in {Neural} {Networks}},
volume = {31},
issn = {0899-7667, 1530-888X},
shorttitle = {Vector-{Derived} {Transformation} {Binding}},
url = {https://www.mitpressjournals.org/doi/abs/10.1162/neco_a_01179},
doi = {10.1162/neco_a_01179},
abstract = {We present a new binding operation, vector-derived transformation binding (VTB), for use in vector symbolic architectures (VSA). The performance of VTB is compared to circular convolution, used in holographic reduced representations (HRRs), in terms of list and stack encoding capacity. A special focus is given to the possibility of a neural implementation by the means of the Neural Engineering Framework (NEF). While the scaling of required neural resources is slightly worse for VTB, it is found to be on par with circular convolution for list encoding and better for encoding of stacks. Furthermore, VTB influences the vector length less, which also benefits a neural implementation. Consequently, we argue that VTB is an improvement over HRRs for neurally implemented VSAs.},
language = {en},
number = {5},
urldate = {2021-03-07},
journal = {Neural Computation},
author = {Gosmann, Jan and Eliasmith, Chris},
month = may,
year = {2019},
note = {Publisher: MIT Press},
pages = {849--869},
annote = {Publisher: MIT Press},
file = {Gosmann_Eliasmith_2019_Vector-Derived_Transformation_Binding.pdf:files/5685/Gosmann_Eliasmith_2019_Vector-Derived_Transformation_Binding.pdf:application/pdf;Snapshot:files/5706/neco_a_01179.html:text/html},
}
@article{sado_explainable_2021,
title = {Explainable {Goal}-{Driven} {Agents} and {Robots}: {A} {Comprehensive} {Review}},
url = {http://arxiv.org/abs/2004.09705},
abstract = {Recent applications of autonomous agents and robots, such as self-driving cars, scenario-based trainers, exploration robots, and service robots have brought attention to crucial trust-related challenges associated with the current generation of artificial intelligence (AI) systems. AI systems based on the connectionist deep learning neural network approach lack capabilities of explaining their decisions and actions to others, despite their great successes. Without symbolic interpretation capabilities, they are black boxes, which renders their decisions or actions opaque, making it difficult to trust them in safety-critical applications. The recent stance on the explainability of AI systems has witnessed several approaches on eXplainable Artificial Intelligence (XAI); however, most of the studies have focused on data-driven XAI systems applied in computational sciences. Studies addressing the increasingly pervasive goal-driven agents and robots are still missing. This paper reviews approaches on explainable goal-driven intelligent agents and robots, focusing on techniques for explaining and communicating agents perceptual functions (example, senses, and vision) and cognitive reasoning (example, beliefs, desires, intention, plans, and goals) with humans in the loop. The review highlights key strategies that emphasize transparency, understandability, and continual learning for explainability. Finally, the paper presents requirements for explainability and suggests a roadmap for the possible realization of effective goal-driven explainable agents and robots.},
language = {en},
urldate = {2021-03-07},
journal = {arXiv:2004.09705 [cs]},
author = {Sado, Fatai and Loo, Chu Kiong and Liew, Wei Shiung and Kerzel, Matthias and Wermter, Stefan},
month = jan,
year = {2021},
note = {arXiv: 2004.09705},
keywords = {Artificial intelligence, Computer Science - Robotics},
pages = {41},
file = {arXiv.org Snapshot:files/5702/2004.html:text/html;Sado_et_al_2021_Explainable_Goal-Driven_Agents_and_Robots.pdf:files/5680/Sado_et_al_2021_Explainable_Goal-Driven_Agents_and_Robots.pdf:application/pdf},
}
@inproceedings{tous_vector_2006,
address = {Berlin, Heidelberg},
series = {Lecture {Notes} in {Computer} {Science}},
title = {A {Vector} {Space} {Model} for {Semantic} {Similarity} {Calculation} and {OWL} {Ontology} {Alignment}},
isbn = {978-3-540-37872-3},
doi = {10.1007/11827405_30},
abstract = {Ontology alignment (or matching) is the operation that takes two ontologies and produces a set of semantic correspondences (usually semantic similarities) between some elements of one of them and some elements of the other. A rigorous, efficient and scalable similarity measure is a pre-requisite of an ontology alignment process. This paper presents a semantic similarity measure based on a matrix represention of nodes from an RDF labelled directed graph. An entity is described with respect to how it relates to other entities using N-dimensional vectors, being N the number of selected external predicates. We adapt a known graph matching algorithm when applying this idea to the alignment of two ontologies. We have successfully tested the model with the public testcases of the Ontology Alignment Evaluation Initiative 2005.},
language = {en},
booktitle = {Database and {Expert} {Systems} {Applications}},
publisher = {Springer},
author = {Tous, Rubén and Delgado, Jaime},
editor = {Bressan, Stéphane and Küng, Josef and Wagner, Roland},
year = {2006},
keywords = {Bipartite Graph, Resource Description Framework, Semantic Similarity, Semantic Similarity Measure, Vector Space Model},
pages = {307--316},
file = {Tous_Delgado_2006_A_Vector_Space_Model_for_Semantic_Similarity_Calculation_and_OWL_Ontology.pdf:files/5720/Tous_Delgado_2006_A_Vector_Space_Model_for_Semantic_Similarity_Calculation_and_OWL_Ontology.pdf:application/pdf},
}
@article{phan_ontology-based_2017,
title = {Ontology-based deep learning for human behavior prediction with explanations in health social networks},
volume = {384},
issn = {0020-0255},
url = {https://www.sciencedirect.com/science/article/pii/S0020025516306090},
doi = {10.1016/j.ins.2016.08.038},
abstract = {Human behavior modeling is a key component in application domains such as healthcare and social behavior research. In addition to accurate prediction, having the capacity to understand the roles of human behavior determinants and to provide explanations for the predicted behaviors is also important. Having this capacity increases trust in the systems and the likelihood that the systems actually will be adopted, thus driving engagement and loyalty. However, most prediction models do not provide explanations for the behaviors they predict. In this paper, we study the research problem, human behavior prediction with explanations, for healthcare intervention systems in health social networks. We propose an ontology-based deep learning model (ORBM+) for human behavior prediction over undirected and nodes-attributed graphs. We first propose a bottom-up algorithm to learn the user representation from health ontologies. Then the user representation is utilized to incorporate self-motivation, social influences, and environmental events together in a human behavior prediction model, which extends a well-known deep learning method, the Restricted Boltzmann Machine. ORBM+ not only predicts human behaviors accurately, but also, it generates explanations for each predicted behavior. Experiments conducted on both real and synthetic health social networks have shown the tremendous effectiveness of our approach compared with conventional methods.},
language = {en},
urldate = {2021-03-07},
journal = {Information Sciences},
author = {Phan, Nhathai and Dou, Dejing and Wang, Hao and Kil, David and Piniewski, Brigitte},
month = apr,
year = {2017},
keywords = {Deep learning, Health informatics, Ontology, Social network},
pages = {298--313},
file = {Phan_et_al_2017_Ontology-based_deep_learning_for_human_behavior_prediction_with_explanations_in.pdf:files/5728/Phan_et_al_2017_Ontology-based_deep_learning_for_human_behavior_prediction_with_explanations_in.pdf:application/pdf;ScienceDirect Snapshot:files/5727/S0020025516306090.html:text/html},
}
@article{hohenecker_ontology_2020,
title = {Ontology {Reasoning} with {Deep} {Neural} {Networks}},
volume = {68},
issn = {1076-9757},
url = {http://arxiv.org/abs/1808.07980},
doi = {10.1613/jair.1.11661},
abstract = {The ability to conduct logical reasoning is a fundamental aspect of intelligent human behavior, and thus an important problem along the way to human-level artificial intelligence. Traditionally, logic-based symbolic methods from the field of knowledge representation and reasoning have been used to equip agents with capabilities that resemble human logical reasoning qualities. More recently, however, there has been an increasing interest in using machine learning rather than logic-based symbolic formalisms to tackle these tasks. In this paper, we employ state-of-the-art methods for training deep neural networks to devise a novel model that is able to learn how to effectively perform logical reasoning in the form of basic ontology reasoning. This is an important and at the same time very natural logical reasoning task, which is why the presented approach is applicable to a plethora of important real-world problems. We present the outcomes of several experiments, which show that our model is able to learn to perform highly accurate ontology reasoning on very large, diverse, and challenging benchmarks. Furthermore, it turned out that the suggested approach suffers much less from different obstacles that prohibit logic-based symbolic reasoning, and, at the same time, is surprisingly plausible from a biological point of view.},
urldate = {2021-03-07},
journal = {Journal of Artificial Intelligence Research},
author = {Hohenecker, Patrick and Lukasiewicz, Thomas},
month = jul,
year = {2020},
note = {arXiv: 1808.07980},
keywords = {Artificial intelligence},
file = {arXiv.org Snapshot:files/5736/1808.html:text/html;Hohenecker_Lukasiewicz_2020_Ontology_Reasoning_with_Deep_Neural_Networks.pdf:files/5737/Hohenecker_Lukasiewicz_2020_Ontology_Reasoning_with_Deep_Neural_Networks.pdf:application/pdf},
}
@article{levesque_knowledge_1986,
title = {Knowledge {Representation} and {Reasoning}},
volume = {1},
issn = {8756-7016},
url = {https://www.annualreviews.org/doi/10.1146/annurev.cs.01.060186.001351},
doi = {10.1146/annurev.cs.01.060186.001351},
number = {1},
urldate = {2021-03-07},
journal = {Annual Review of Computer Science},
author = {Levesque, H J},
month = jun,
year = {1986},
note = {Publisher: Annual Reviews},
pages = {255--287},
annote = {\_eprint: https://doi.org/10.1146/annurev.cs.01.060186.001351},
file = {Snapshot:files/5734/annurev.cs.01.060186.html:text/html},
}
@article{garcez_towards_2018,
title = {Towards {Symbolic} {Reinforcement} {Learning} with {Common} {Sense}},
url = {http://arxiv.org/abs/1804.08597},
abstract = {Deep Reinforcement Learning (deep RL) has made several breakthroughs in recent years in applications ranging from complex control tasks in unmanned vehicles to game playing. Despite their success, deep RL still lacks several important capacities of human intelligence, such as transfer learning, abstraction and interpretability. Deep Symbolic Reinforcement Learning (DSRL) seeks to incorporate such capacities to deep Q-networks (DQN) by learning a relevant symbolic representation prior to using Q-learning. In this paper, we propose a novel extension of DSRL, which we call Symbolic Reinforcement Learning with Common Sense (SRL+CS), offering a better balance between generalization and specialization, inspired by principles of common sense when assigning rewards and aggregating Q-values. Experiments reported in this paper show that SRL+CS learns consistently faster than Q-learning and DSRL, achieving also a higher accuracy. In the hardest case, where agents were trained in a deterministic environment and tested in a random environment, SRL+CS achieves nearly 100\% average accuracy compared to DSRL's 70\% and DQN's 50\% accuracy. To the best of our knowledge, this is the first case of near perfect zero-shot transfer learning using Reinforcement Learning.},
urldate = {2021-03-08},
journal = {arXiv:1804.08597 [cs, stat]},
author = {Garcez, Artur d'Avila and Dutra, Aimore Resende Riquetti and Alonso, Eduardo},
month = apr,
year = {2018},
note = {arXiv: 1804.08597},
keywords = {Statistics - Machine Learning, Artificial intelligence, I.2.6, Machine Learning},
annote = {Comment: 15 pages, 13 figures, 26 references},
file = {arXiv.org Snapshot:files/5866/1804.html:text/html;Garcez_et_al_2018_Towards_Symbolic_Reinforcement_Learning_with_Common_Sense.pdf:files/5868/Garcez_et_al_2018_Towards_Symbolic_Reinforcement_Learning_with_Common_Sense.pdf:application/pdf},
}
@article{garnelo_towards_2016,
title = {Towards {Deep} {Symbolic} {Reinforcement} {Learning}},
url = {http://arxiv.org/abs/1609.05518},
abstract = {Deep reinforcement learning (DRL) brings the power of deep neural networks to bear on the generic task of trial-and-error learning, and its effectiveness has been convincingly demonstrated on tasks such as Atari video games and the game of Go. However, contemporary DRL systems inherit a number of shortcomings from the current generation of deep learning techniques. For example, they require very large datasets to work effectively, entailing that they are slow to learn even when such datasets are available. Moreover, they lack the ability to reason on an abstract level, which makes it difficult to implement high-level cognitive functions such as transfer learning, analogical reasoning, and hypothesis-based reasoning. Finally, their operation is largely opaque to humans, rendering them unsuitable for domains in which verifiability is important. In this paper, we propose an end-to-end reinforcement learning architecture comprising a neural back end and a symbolic front end with the potential to overcome each of these shortcomings. As proof-of-concept, we present a preliminary implementation of the architecture and apply it to several variants of a simple video game. We show that the resulting system -- though just a prototype -- learns effectively, and, by acquiring a set of symbolic rules that are easily comprehensible to humans, dramatically outperforms a conventional, fully neural DRL system on a stochastic variant of the game.},
urldate = {2021-03-08},
journal = {arXiv:1609.05518 [cs]},
author = {Garnelo, Marta and Arulkumaran, Kai and Shanahan, Murray},
month = oct,
year = {2016},
note = {arXiv: 1609.05518},
keywords = {Artificial intelligence, Machine Learning},
file = {arXiv.org Snapshot:files/5870/1609.html:text/html;Garnelo_et_al_2016_Towards_Deep_Symbolic_Reinforcement_Learning.pdf:files/5871/Garnelo_et_al_2016_Towards_Deep_Symbolic_Reinforcement_Learning.pdf:application/pdf},
}
@article{anderson_neurosymbolic_2020,
title = {Neurosymbolic {Reinforcement} {Learning} with {Formally} {Verified} {Exploration}},
url = {http://arxiv.org/abs/2009.12612},
abstract = {We present Revel, a partially neural reinforcement learning (RL) framework for provably safe exploration in continuous state and action spaces. A key challenge for provably safe deep RL is that repeatedly verifying neural networks within a learning loop is computationally infeasible. We address this challenge using two policy classes: a general, neurosymbolic class with approximate gradients and a more restricted class of symbolic policies that allows efficient verification. Our learning algorithm is a mirror descent over policies: in each iteration, it safely lifts a symbolic policy into the neurosymbolic space, performs safe gradient updates to the resulting policy, and projects the updated policy into the safe symbolic subset, all without requiring explicit verification of neural networks. Our empirical results show that Revel enforces safe exploration in many scenarios in which Constrained Policy Optimization does not, and that it can discover policies that outperform those learned through prior approaches to verified exploration.},
urldate = {2021-03-08},
journal = {arXiv:2009.12612 [cs, stat]},
author = {Anderson, Greg and Verma, Abhinav and Dillig, Isil and Chaudhuri, Swarat},
month = oct,
year = {2020},
note = {arXiv: 2009.12612},
keywords = {Statistics - Machine Learning, Machine Learning},
file = {Anderson_et_al_2020_Neurosymbolic_Reinforcement_Learning_with_Formally_Verified_Exploration.pdf:files/5869/Anderson_et_al_2020_Neurosymbolic_Reinforcement_Learning_with_Formally_Verified_Exploration.pdf:application/pdf;arXiv.org Snapshot:files/5867/2009.html:text/html},
}
@article{ma_interpretable_2020,
title = {Interpretable {Reinforcement} {Learning} {With} {Neural} {Symbolic} {Logic}},
url = {https://openreview.net/forum?id=M_gk45ItxIp},
abstract = {Recent progress in deep reinforcement learning (DRL) can be largely attributed to the use of neural networks. However, this black-box approach fails to explain the learned policy in a human...},
language = {en},
urldate = {2021-03-08},
journal = {ICLR 2021 Ninth International Conference on Learning Representations},
author = {Ma, Zhihao and Zhuang, Yuzheng and Weng, Paul and Li, Dong and Shao, Kun and Liu, Wulong and Zhuo, Hankz Hankui and Hao, Jianye},
month = sep,
year = {2020},
file = {Ma_et_al_2020_Interpretable_Reinforcement_Learning_With_Neural_Symbolic_Logic.pdf:files/5875/Ma_et_al_2020_Interpretable_Reinforcement_Learning_With_Neural_Symbolic_Logic.pdf:application/pdf;Snapshot:files/5874/forum.html:text/html},
}
@misc{harris_deep_2020,
title = {Deep reinforcement learning, symbolic learning and the road to {AGI}},
url = {https://towardsdatascience.com/language-models-symbolic-learning-and-the-road-to-agi-75725985cdf7},
abstract = {Tim Rocktäschel on the TDS podcast},
language = {en},
urldate = {2021-03-08},
journal = {Medium},
author = {Harris, Jeremie},
month = nov,
year = {2020},
file = {Snapshot:files/5881/language-models-symbolic-learning-and-the-road-to-agi-75725985cdf7.html:text/html},
}
@techreport{denet_dispositif_2020,
type = {report},
title = {Le dispositif {Tabletop} du projet {AIDE} : développement de son interface utilisateur.},
shorttitle = {Le dispositif {Tabletop} du projet {AIDE}},
url = {https://hal.inria.fr/hal-02935633},
abstract = {Le travail présenté ici consiste en la création d'une interface ludique et interactive pour un serious game qui est une des actions du projet : Artificial Intelligence Devoted to Education\vphantom{\{}\}(AIDE). Ce projet a pour but de permettre le développement de la pensée computationnelle (ou pensée informatique) et d'en étudier les mécanismes d'apprentissage par des techniques, ou approches, basés sur les neurosciences cognitives et les sciences de l'éducation. L'expérience d'apprentissage passe par un jeu d'évasion (escape game) sur table utilisant des composants électroniques et des outils issus de la robotique. L'interface est visualisée sur un écran avec un processeur à bas coût. Elle se présente sous forme de pages Web. Le jeu communique avec l'interface en utilisant un serveur local et des techniques d'apprentissage automatique ou apprentissage machine (machine learning). Les interactions entre l'apprenant et la table de jeu sont filmées et analysées en temps réel, pour être affichée au sein de l'interface et enregistrées. Cette dernière est aussi chargée de transmettre les indications et les éléments scénarisés du jeu. La créativité, l'imagination et les compétences de l'apprenant sont ainsi sollicitées et évaluées.},
language = {fr},
urldate = {2021-03-08},
institution = {Inria Bordeaux Sud-Ouest},
author = {Denet, Lola},
month = sep,
year = {2020},
pages = {14},
file = {Denet_2020_Le dispositif Tabletop du projet AIDE.pdf:files/6721/Denet_2020_Le dispositif Tabletop du projet AIDE.pdf:application/pdf;Denet_2020_Le_dispositif_Tabletop_du_projet_AIDE.pdf:files/5883/Denet_2020_Le_dispositif_Tabletop_du_projet_AIDE.pdf:application/pdf;Snapshot:files/5882/hal-02935633.html:text/html;Snapshot:files/6788/hal-02935633.html:text/html},
}
@book{musial_precis_2020,
edition = {1st},
series = {{PEDAGOGIES} {EN} {DEVELOPPEMENT}},
title = {Précis d'ingénierie pédagogique},
isbn = {978-2-8073-2419-0},
abstract = {Cet ouvrage propose une théorie de l'ingénierie pédagogique en 3 actes : l'acte d'apprendre, l'acte d'enseigner et l'acte de concevoir un enseignement. Cette théorie est ensuite appliquée à 11 disciplines et niveaux d'enseignement très diversifiés.},
language = {fr},
publisher = {De Boeck Supérieur},
author = {Musial, Manuel and Tricot, André},
month = feb,
year = {2020},
file = {Snapshot:files/5887/9782807324190-precis-d-ingenierie-pedagogique.html:text/html},
}
@misc{brown_metacognitionpng_1987,
title = {metacognition.png},
url = {https://joanakompa.files.wordpress.com/2017/08/overview.png},
urldate = {2020-10-29},
author = {Brown, Ann},
year = {1987},
file = {metacognition.png:files/5888/metacognition.png:image/png},
}
@book{newell_human_1972,
address = {Englewood Cliffs, N.J.},
title = {Human problem solving},
language = {English},
urldate = {2021-03-09},
publisher = {Prentice-Hall},
author = {Newell, Allen and Simon, Herbert A},
year = {1972},
note = {OCLC: 622041645},
file = {Newell_Simon_1972_Human_problem_solving.pdf:files/5890/Newell_Simon_1972_Human_problem_solving.pdf:application/pdf;Newell_Simon_1972_Human_problem_solving.pdf:files/5892/Newell_Simon_1972_Human_problem_solving.pdf:application/pdf},
}
@misc{noauthor_protegeprojectprotege_2021,
title = {protegeproject/protege},
copyright = {View license , View license},
url = {https://github.com/protegeproject/protege},
abstract = {Protege Desktop. Contribute to protegeproject/protege development by creating an account on GitHub.},
urldate = {2021-03-10},
publisher = {Protégé Project},
month = mar,
year = {2021},
note = {original-date: 2013-08-20T01:26:26Z},
}
@misc{noauthor_protegeprojectsnap-sparql-query_2020,
title = {protegeproject/snap-sparql-query},
copyright = {LGPL-3.0 License , LGPL-3.0 License},
url = {https://github.com/protegeproject/snap-sparql-query},
abstract = {An API for parsing SPARQL queries. Contribute to protegeproject/snap-sparql-query development by creating an account on GitHub.},
urldate = {2021-03-10},
publisher = {Protégé Project},
month = nov,
year = {2020},
note = {original-date: 2015-03-10T21:56:19Z},
}
@article{moors_role_2019,
title = {The role of stimulus-driven versus goal-directed processes in fight and flight tendencies measured with motor evoked potentials induced by {Transcranial} {Magnetic} {Stimulation}},
volume = {14},
issn = {1932-6203},
url = {https://dx.plos.org/10.1371/journal.pone.0217266},
doi = {10.1371/journal.pone.0217266},
abstract = {This study examines two contrasting explanations for early tendencies to fight and flee. According to a stimulus-driven explanation, goal-incompatible stimuli that are easy/difficult to control lead to the tendency to fight/flee. According to a goal-directed explanation, on the other hand, the tendency to fight/flee occurs when the expected utility of fighting/fleeing is the highest. Participants did a computer task in which they were confronted with goal-incompatible stimuli that were (a) easy to control and fighting had the highest expected utility, (b) easy to control and fleeing had the highest expected utility, and (c) difficult to control and fleeing and fighting had zero expected utility. After participants were trained to use one hand to fight and another hand to flee, they either had to choose a response or merely observe the stimuli. During the observation trials, single-pulse Transcranial Magnetic Stimulation (TMS) was applied to the primary motor cortex 450 ms post-stimulus onset and motorevoked potentials (MEPs) were measured from the hand muscles. Results showed that participants chose to fight/flee when the expected utility of fighting/fleeing was the highest, and that they responded late when the expected utility of both responses was low. They also showed larger MEPs for the right/left hand when the expected utility of fighting/fleeing was the highest. This result can be interpreted as support for the goal-directed account, but only if it is assumed that we were unable to override the presumed natural mapping between hand (right/left) and response (fight/flight).},
language = {en},
number = {5},
urldate = {2021-03-09},
journal = {PLOS ONE},
author = {Moors, Agnes and Fini, Chiara and Everaert, Tom and Bardi, Lara and Bossuyt, Evelien and Kuppens, Peter and Brass, Marcel},
editor = {Avenanti, Alessio},
month = may,
year = {2019},
pages = {e0217266},
file = {Moors_et_al_2019_The_role_of_stimulus-driven_versus_goal-directed_processes_in_fight_and_flight.pdf:files/5900/Moors_et_al_2019_The_role_of_stimulus-driven_versus_goal-directed_processes_in_fight_and_flight.pdf:application/pdf},
}
@article{flum_exploratory_2006,
title = {Exploratory {Orientation} as an {Educational} {Goal}},
doi = {10.1207/s15326985ep4102_3},
abstract = {This article lays the foundations for the notion of exploratory orientation as an educational goal. After reviewing the conceptual roots of exploration, the article examines the essence of the experience of exploration and its developmental benefits. Then, turning to the context of school, the article discusses the mostly implicit role of exploration and of exploratory orientation in a number of perspectives concerned with adaptive student engagement. The article concludes by briefly noting the environmental and instructional practices that could facilitate an exploratory orientation among students, and by calling for further conceptual and empirical work in this domain.},
author = {Flum, Hanoch and Kaplan, Avi},
year = {2006},
file = {Flum_Kaplan_2006_Exploratory_Orientation_as_an_Educational_Goal.pdf:files/6053/Flum_Kaplan_2006_Exploratory_Orientation_as_an_Educational_Goal.pdf:application/pdf},
}
@article{kaplan_achievement_2010,
title = {Achievement goal orientations and identity formation styles},
volume = {5},
issn = {1747-938X},
url = {https://www.sciencedirect.com/science/article/pii/S1747938X09000347},
doi = {10.1016/j.edurev.2009.06.004},
abstract = {The present article points to shared underlying theoretical assumptions and central processes of a prominent academic motivation perspective – achievement goal theory – and recent process perspectives in the identity formation literature, and more specifically, identity formation styles. The review highlights the shared definition of achievement goal orientations and identity formation styles as mental frames that guide interpretation of situations, define standards for action, and direct coping with challenges. Despite differences in unit-of-analysis and general focus, both perspectives emphasize the qualitative differences between mental frames that are oriented towards self-development and those that are oriented towards self-worth validation and enhancement. Also, recent theorizing in both perspectives highlights the role of contexts and situations in adolescents’ adoption of certain achievement goal orientations and identity formation styles. The article concludes with research questions concerning the potential reciprocal relations between adolescents’ academic achievement goal orientations and identity formation styles.},
language = {en},
number = {1},
urldate = {2021-03-09},
journal = {Educational Research Review},
author = {Kaplan, Avi and Flum, Hanoch},
month = jan,
year = {2010},
keywords = {School, Motivation, Adolescence, Identity formation},
pages = {50--67},
file = {Kaplan_Flum_2010_Achievement_goal_orientations_and_identity_formation_styles.pdf:files/5903/Kaplan_Flum_2010_Achievement_goal_orientations_and_identity_formation_styles.pdf:application/pdf;ScienceDirect Snapshot:files/5902/S1747938X09000347.html:text/html},
}
@inproceedings{mercier_ontology_2021,
title = {Ontology as neuronal-space manifold: towards symbolic and numerical artificial embedding},
shorttitle = {Ontology as neuronal-space manifold},
abstract = {Some human cognitive tasks may involve tightly interleaved logical and numerical computations. On the one hand, ontologies allow us to describe symbolic structured knowledge and perform logical inference, providing a rather natural representation of human reasoning as modeled in cognitive psychology. On the other hand, spiking neural networks are a biologically plausible implementation of processing in brain circuits, yet they process numeric vectors rather than symbolic data. Unifying these symbolic and sub-symbolic approaches is still a wide and open question, and the Semantic Pointer Architecture (SPA) based on the Vector Symbolic Architecture (VSA) provides a way to manipulate symbols embedded as numeric vectors that carry semantic information.
In this paper, as a step towards filling the symbolic/numerical gap, we propose to map an ontology onto a SPA-based architecture with a preliminary partial implementation into spiking neural networks. More specifically, we focus on ontology standards used in the semantic web such as Resource Description Framework [Schema] (RDF[S]) and the Web Ontology Language (OWL). We provide a detailed implementation example in the case of specific RDFS entailments based on predicate chaining. To that end, we used the neural simulator Nengo with two associative memories in interaction, the first one storing assertions and the second one storing entailment rules. Reporting interesting formal results, our embedding enjoys intrinsic properties allowing semantic reasoning through distributed numerical computing. This original preliminary work thus combines symbolic and numerical approaches for cognitive modeling, which might be useful to model some complex human tasks such as ill-defined problem-solving, involving neuronal knowledge manipulation.},
booktitle = {{KRHCAI}-21@{KR2021}},
author = {Mercier, Chloé and Chateau-Laurent, Hugo and Alexandre, Frederic and Viéville, Thierry},
month = mar,
year = {2021},
file = {Mercier_et_al_2021_Ontology_as_neuronal-space_manifold.pdf:files/7034/Mercier_et_al_2021_Ontology_as_neuronal-space_manifold.pdf:application/pdf},
}
@article{abbes_modular_2018,
title = {Modular {Ontologies} {Composition}: {Levenshtein}-{Distance}-{Based} {Concepts} {Structure} {Comparison}},
volume = {13},
issn = {1554-1045},
shorttitle = {Modular {Ontologies} {Composition}},
url = {https://doi.org/10.4018/IJITWE.2018100103},
doi = {10.4018/IJITWE.2018100103},
abstract = {This article describes how a modular ontology is a set of interconnected ontology modules. Modularity is a key requirement for collaborative ontology engineering and for distributed ontology reuse on the Web. Combining ontology modules in this context to get a global ontology is an important issue since it requires to resolves mismatches between the compared concepts. This article proposes a novel approach to automatically compose ontology modules. The proposed approach is based on concept structure comparison. The algorithm allowing to merge the ontology modules into a global ontology is detailed and similarity measures are explained. Similarity measures are computed against concept names, attributes and relationships. Experiments performed to test this algorithm are described and evaluation results are equally discussed.},
number = {4},
urldate = {2021-03-09},
journal = {International Journal of Information Technology and Web Engineering},
author = {Abbes, Hanen and Gargouri, Faïez},
month = oct,
year = {2018},
keywords = {Ontology, Concept Structure, Concepts Merging, Levenshtein Distance, Modular Ontology, Modules Composition, Similarity Measures},
pages = {35--60},
}
@book{stoilos_string_2005,
title = {A {String} {Metric} for {Ontology} {Alignment}},
volume = {3729},
isbn = {978-3-540-29754-3},
abstract = {Ontologies are today a key part of every knowledge based system. They provide a source of shared and precisely defined terms, resulting in system interoperability by knowledge sharing and reuse. Un- fortunately, the variety of ways that a domain can be conceptualized results in the creation of different ontologies with contradicting or over- lapping parts. For this reason ontologies need to be brought into mutual agreement (aligned). One important method for ontology alignment is the comparison of class and property names of ontologies using string- distance metrics. Today quite a lot of such metrics exist in literature. But all of them have been initially developed for different applications and fields, resulting in poor performance when applied in this new domain. In the current paper we present a new string metric for the comparison of names which performs better on the process of ontology alignment as well as to many other field matching problems.},
author = {Stoilos, Giorgos and Stamou, Giorgos and Kollias, Stefanos},
month = nov,
year = {2005},
doi = {10.1007/11574620_45},
note = {Pages: 637},
file = {Stoilos_et_al_2005_A_String_Metric_for_Ontology_Alignment.pdf:files/5918/Stoilos_et_al_2005_A_String_Metric_for_Ontology_Alignment.pdf:application/pdf},
}
@article{shvaiko_ontology_2013,
title = {Ontology matching: state of the art and future challenges},
volume = {25},
shorttitle = {Ontology matching},
url = {https://hal.inria.fr/hal-00917910},
doi = {10.1109/TKDE.2011.253},
abstract = {After years of research on ontology matching, it is reasonable to consider several questions: is the field of ontology matching still making progress? Is this progress significant enough to pursue some further research? If so, what are the particularly promising directions? To answer these questions, we review the state of the art of ontology matching and analyze the results of recent ontology matching evaluations. These results show a measurable improvement in the field, the speed of which is albeit slowing down. We conjecture that significant improvements can be obtained only by addressing important challenges for ontology matching. We present such challenges with insights on how to approach them, thereby aiming to direct research into the most promising tracks and to facilitate the progress of the field.},
language = {en},
number = {1},
urldate = {2021-03-10},
journal = {IEEE Transactions on Knowledge and Data Engineering},
author = {Shvaiko, Pavel and Euzenat, Jérôme},
year = {2013},
pages = {158},
file = {Shvaiko_Euzenat_2013_Ontology_matching.pdf:files/5924/Shvaiko_Euzenat_2013_Ontology_matching.pdf:application/pdf;Snapshot:files/5925/hal-00917910.html:text/html},
}
@article{bille_survey_2005,
title = {A survey on tree edit distance and related problems},
volume = {337},
issn = {0304-3975},
url = {https://www.sciencedirect.com/science/article/pii/S0304397505000174},
doi = {10.1016/j.tcs.2004.12.030},
abstract = {We survey the problem of comparing labeled trees based on simple local operations of deleting, inserting, and relabeling nodes. These operations lead to the tree edit distance, alignment distance, and inclusion problem. For each problem we review the results available and present, in detail, one or more of the central algorithms for solving the problem.},
language = {en},
number = {1},
urldate = {2021-03-08},
journal = {Theoretical Computer Science},
author = {Bille, Philip},
month = jun,
year = {2005},
keywords = {Tree alignment, Tree edit distance, Tree inclusion, Tree matching},
pages = {217--239},
file = {Bille_2005_A_survey_on_tree_edit_distance_and_related_problems.pdf:files/5939/Bille_2005_A_survey_on_tree_edit_distance_and_related_problems.pdf:application/pdf;ScienceDirect Snapshot:files/5940/S0304397505000174.html:text/html},
}
@article{rmus_role_2021,
title = {The role of executive function in shaping reinforcement learning},
volume = {38},
issn = {2352-1546},
url = {https://www.sciencedirect.com/science/article/pii/S2352154620301480},
doi = {10.1016/j.cobeha.2020.10.003},
abstract = {Reinforcement learning (RL) models have advanced our understanding of how animals learn and make decisions, and how the brain supports learning. However, the neural computations that are explained by RL algorithms fall short of explaining many sophisticated aspects of human learning and decision making, including the generalization of behavior to novel contexts, one-shot learning, and the synthesis of task information in complex environments. Instead, these aspects of behavior are assumed to be supported by the brain’s executive functions (EF). We review recent findings that highlight the importance of EF in instrumental learning. Specifically, we advance the theory that EF sets the stage for canonical RL computations in the brain, providing inputs that broaden their flexibility and applicability. Our theory has important implications for how to interpret RL computations in both brain and behavior.},
language = {en},
urldate = {2021-03-14},
journal = {Current Opinion in Behavioral Sciences},
author = {Rmus, Milena and McDougle, Samuel D and Collins, Anne GE},
month = apr,
year = {2021},
pages = {66--73},
file = {Rmus_et_al_2021_The_role_of_executive_function_in_shaping_reinforcement_learning.pdf:files/5953/Rmus_et_al_2021_The_role_of_executive_function_in_shaping_reinforcement_learning.pdf:application/pdf;ScienceDirect Snapshot:files/5954/S2352154620301480.html:text/html},
}
@article{ouangraoua_constrained_2009,
title = {A {Constrained} {Edit} {Distance} {Algorithm} {Between} {Semi}-ordered {Trees}},
volume = {410},
url = {https://hal.archives-ouvertes.fr/hal-00350113},
doi = {10.1016/j.tcs.2008.11.022},
abstract = {In this paper, we propose a formal definition of a new class of trees called semi-ordered trees and a polynomial dynamic programming algorithm to compute a constrained edit distance between such trees. The core of the method relies on a similar approach to compare unordered (K. Zhang, 1996, Algorithmica, 15:205-222) and ordered trees (K. Zhang, 1995, Pattern recognition, 28(3):463-474). The method is currently applied to evaluate the similarity between architectures of apple trees (Segura et al., 2007, Euphytica, in press).},
number = {8-10},
urldate = {2021-03-16},
journal = {Theoretical Computer Science},
author = {Ouangraoua, Aida and Ferraro, Pascal},
year = {2009},
note = {Publisher: Elsevier},
pages = {837--846},
file = {HAL Snapshot:files/6019/hal-00350113.html:text/html},
}
@article{blumenthal_new_2019,
title = {New {Techniques} for {Graph} {Edit} {Distance} {Computation}},
url = {http://arxiv.org/abs/1908.00265},
abstract = {Due to their capacity to encode rich structural information, labeled graphs are often used for modeling various kinds of objects such as images, molecules, and chemical compounds. If pattern recognition problems such as clustering and classification are to be solved on these domains, a (dis-)similarity measure for labeled graphs has to be defined. A widely used measure is the graph edit distance (GED), which, intuitively, is defined as the minimum amount of distortion that has to be applied to a source graph in order to transform it into a target graph. The main advantage of GED is its flexibility and sensitivity to small differences between the input graphs. Its main drawback is that it is hard to compute. In this thesis, new results and techniques for several aspects of computing GED are presented. Firstly, theoretical aspects are discussed: competing definitions of GED are harmonized, the problem of computing GED is characterized in terms of complexity, and several reductions from GED to the quadratic assignment problem (QAP) are presented. Secondly, solvers for the linear sum assignment problem with error-correction (LSAPE) are discussed. LSAPE is a generalization of the well-known linear sum assignment problem (LSAP), and has to be solved as a subproblem by many GED algorithms. In particular, a new solver is presented that efficiently reduces LSAPE to LSAP. Thirdly, exact algorithms for computing GED are presented in a systematic way, and improvements of existing algorithms as well as a new mixed integer programming (MIP) based approach are introduced. Fourthly, a detailed overview of heuristic algorithms that approximate GED via upper and lower bounds is provided, and eight new heuristics are described. Finally, a new easily extensible C++ library for exactly or approximately computing GED is presented.},
urldate = {2021-03-16},
journal = {arXiv:1908.00265 [cs]},
author = {Blumenthal, David B.},
month = aug,
year = {2019},
note = {arXiv: 1908.00265},
keywords = {Computer Vision and Pattern Recognition, Data Structures and Algorithms},
annote = {Comment: Ph.D. Thesis, Free University of Bozen-Bolzano},
file = {arXiv.org Snapshot:files/6023/1908.html:text/html;Blumenthal_2019_New_Techniques_for_Graph_Edit_Distance_Computation.pdf:files/6022/Blumenthal_2019_New_Techniques_for_Graph_Edit_Distance_Computation.pdf:application/pdf},
}
@article{clemente_proposal_2011,
title = {A proposal for student modeling based on ontologies and diagnosis rules},
volume = {38},
issn = {0957-4174},
url = {https://www.sciencedirect.com/science/article/pii/S0957417410015095},
doi = {10.1016/j.eswa.2010.12.146},
abstract = {The advances in the educational field and the high complexity of student modeling have provoked it to be one of the aspects more investigated in Intelligent Tutoring Systems (ITSs). The Student Models (SMs) should not only represent the student’s knowledge, but rather they should reflect, as faithfully as possible, the student’s reasoning process. To facilitate this goal, in this article a new approach to student modeling is proposed that benefits from the advantages of Ontological Engineering, advancing in the pursue of a more granular and complete knowledge representation. It’s focused, mainly, on the SM cognitive diagnosis process, and we present a method providing a rich diagnosis about the student’s knowledge state – especially, about the state of learning objectives reached or not. The main goal is to achieve SMs with a good adaptability to the student’s features and a high flexibility for its integration in varied ITSs.},
language = {en},
number = {7},
urldate = {2021-04-06},
journal = {Expert Systems with Applications},
author = {Clemente, Julia and Ramírez, Jaime and de Antonio, Angélica},
month = jul,
year = {2011},
keywords = {Intelligent Tutoring System, Pedagogic diagnosis, Student model, Virtual environments for training},
pages = {8066--8078},
file = {Clemente_et_al_2011_A_proposal_for_student_modeling_based_on_ontologies_and_diagnosis_rules.pdf:files/6042/Clemente_et_al_2011_A_proposal_for_student_modeling_based_on_ontologies_and_diagnosis_rules.pdf:application/pdf;ScienceDirect Snapshot:files/6051/S0957417410015095.html:text/html},
}
@incollection{bull_open_2010,
address = {Berlin, Heidelberg},
series = {Studies in {Computational} {Intelligence}},
title = {Open {Learner} {Models}},
isbn = {978-3-642-14363-2},
url = {https://doi.org/10.1007/978-3-642-14363-2_15},
abstract = {An Open Learner Model makes a machines’ representation of the learner available as an important means of support for learning. This means that a suitable interface is created for use by learners, and in some cases for others who aid their learning, including peers, parents and teachers. The chapter describes the range of purposes that Open Learner Models can serve, illustrating these with diverse examples of the ways that they have been made available in several research systems. We then discuss the closely related issues of openness and learner control and the ways that have been explored to support learning by making the learner model available to people other than the learner. This chapter provides a foundation for understanding the range of ways that Open Learner Models have already been used to support learning as well as directions yet to be explored.},
language = {en},
urldate = {2021-04-06},
booktitle = {Advances in {Intelligent} {Tutoring} {Systems}},
publisher = {Springer},
author = {Bull, Susan and Kay, Judy},
editor = {Nkambou, Roger and Bourdeau, Jacqueline and Mizoguchi, Riichiro},
year = {2010},
doi = {10.1007/978-3-642-14363-2_15},
keywords = {Intelligent Tutor System, Learner Control, Learner Model, Student Model, Adaptive Learning Systems},
pages = {301--322},
file = {Bull_Kay_2010_Open_Learner_Models.pdf:files/6043/Bull_Kay_2010_Open_Learner_Models.pdf:application/pdf},
}
@article{abyaa_learner_2019,
title = {Learner modelling: systematic review of the literature from the last 5 years},
volume = {67},
issn = {1556-6501},
shorttitle = {Learner modelling},
url = {https://doi.org/10.1007/s11423-018-09644-1},
doi = {10.1007/s11423-018-09644-1},
abstract = {The field of adaptive e-learning is continuously developing. More research is being conducted in this area as adaptive e-learning aims to provide learners with adaptive learning paths and content, according to their individual characteristics and needs, which makes e-learning more efficient and effective. The learner model, which is a representation of different learner’s characteristics, plays a key role in this adaptation. This paper presents a systematic literature review about learner modelling during the last 5 years, describing the different modelled characteristics and the adopted modelling techniques and modeling types: automatic modeling and collaborative modeling. 107 publications were selected and analyzed, and six categories of the modelled characteristics were identified. This literature review contributes to the identification of the learners’ individual traits and presents the most used modelling techniques for each of them. It also identifies the latest research trends of Learner Modeling and generates future research directions in this field.},
language = {en},
number = {5},
urldate = {2021-04-06},
journal = {Educational Technology Research and Development},
author = {Abyaa, Abir and Khalidi Idrissi, Mohammed and Bennani, Samir},
month = oct,
year = {2019},
pages = {1105--1143},
file = {Abyaa_et_al_2019_Learner_modelling.pdf:files/6044/Abyaa_et_al_2019_Learner_modelling.pdf:application/pdf},
}
@article{hooshyar_open_2020,
title = {Open learner models in supporting self-regulated learning in higher education: {A} systematic literature review},
volume = {154},
issn = {03601315},
shorttitle = {Open learner models in supporting self-regulated learning in higher education},
url = {https://linkinghub.elsevier.com/retrieve/pii/S0360131520300774},
doi = {10.1016/j.compedu.2020.103878},
abstract = {The open learner model (OLM) represents the knowledge or skill levels of learners in various ways, encouraging learners to actively participate in thinking about and crafting their own learning. Despite the important roles that OLMs play in higher education to support the learning process and self-regulated learning (SRL) in particular, there are few studies systematically reviewing OLM technology in higher education, and investigating their potential to foster selfregulated learning. Therefore, we carried out a systematic review of a 30-year sample of OLM studies in higher education and identified 64 articles that study the use of OLMs in supporting SRL. Our findings show that OLMs have been mainly used to support learners’ cognition and a bit less metacognition and motivation; however, emotional support has been rarely provided. The most supported ones are Appraisal and Performance phases; Preparation of learning is enhanced by OLMs not so often. Although learners can edit or negotiate with their learning model in advanced ways, a simple inspectable OLM is more preferred. Reliance on unobservable nodes is less favored in modeling techniques in OLMs because such methods are highly dependent on expert authoring, thereby time-intensive and costly. Comparison and color-coding are two mostused features in OLMs, where the comparison feature is often used for enhancing learners’ engagement and motivation.},
language = {en},
urldate = {2021-04-06},
journal = {Computers \& Education},
author = {Hooshyar, Danial and Pedaste, Margus and Saks, Katrin and Leijen, Äli and Bardone, Emanuele and Wang, Minhong},
month = sep,
year = {2020},
keywords = {Higher education, Open learner model, Self-regulated learning, Systematic review},
pages = {103878},
file = {Hooshyar_et_al_2020_Open_learner_models_in_supporting_self-regulated_learning_in_higher_education.pdf:files/6045/Hooshyar_et_al_2020_Open_learner_models_in_supporting_self-regulated_learning_in_higher_education.pdf:application/pdf;SCOPUS Snapshot:files/6048/display.html:text/html},
}
@inproceedings{cheung_ontology-based_2010,
address = {Berlin, Heidelberg},
series = {Lecture {Notes} in {Computer} {Science}},
title = {An {Ontology}-{Based} {Framework} for {Personalized} {Adaptive} {Learning}},
isbn = {978-3-642-17407-0},
doi = {10.1007/978-3-642-17407-0_6},
abstract = {Adaptive Educational Hypermedia Systems provide an alternative to the “one-size-fits-all” approach to web-based learning. It aims at enhancing e-learning experience with adaptive capabilities to accommodate for the different learning preference and learning aptitude of individual learner. In this paper, we discuss an Ontology-based Framework for Personalized Adaptive Learning (OPAL). Through the development of OPAL, we implemented an online Java programming course, which provides adaptive features through an ontology model and user model relating to user preference, progress and performance. The evaluation with students shows that the adaptive e-learning framework is more effective for university students who have online learning experience.},
language = {en},
booktitle = {Advances in {Web}-{Based} {Learning} – {ICWL} 2010},
publisher = {Springer},
author = {Cheung, Ronnie and Wan, Calvin and Cheng, Calvin},
editor = {Luo, Xiangfeng and Spaniol, Marc and Wang, Lizhe and Li, Qing and Nejdl, Wolfgang and Zhang, Wu},
year = {2010},
keywords = {ontology, e-learning, personalization, Adaptive Learning Systems},
pages = {52--61},
file = {Cheung_et_al_2010_An_Ontology-Based_Framework_for_Personalized_Adaptive_Learning.pdf:files/6047/Cheung_et_al_2010_An_Ontology-Based_Framework_for_Personalized_Adaptive_Learning.pdf:application/pdf},
}
@book{trausan-matu_intelligent_2014,
address = {Cham},
series = {Lecture {Notes} in {Computer} {Science}},
title = {Intelligent {Tutoring} {Systems}: 12th {International} {Conference}, {ITS} 2014, {Honolulu}, {HI}, {USA}, {June} 5-9, 2014. {Proceedings}},
volume = {8474},
isbn = {978-3-319-07220-3 978-3-319-07221-0},
shorttitle = {Intelligent {Tutoring} {Systems}},
url = {http://link.springer.com/10.1007/978-3-319-07221-0},
language = {en},
urldate = {2021-04-06},
publisher = {Springer International Publishing},
editor = {Trausan-Matu, Stefan and Boyer, Kristy Elizabeth and Crosby, Martha and Panourgia, Kitty and Hutchison, David and Kanade, Takeo and Kittler, Josef and Kleinberg, Jon M. and Kobsa, Alfred and Mattern, Friedemann and Mitchell, John C. and Naor, Moni and Nierstrasz, Oscar and Pandu Rangan, C. and Steffen, Bernhard and Terzopoulos, Demetri and Tygar, Doug and Weikum, Gerhard},
year = {2014},
doi = {10.1007/978-3-319-07221-0},
file = {Trausan-Matu_et_al_2014_Intelligent_Tutoring_Systems.pdf:files/6046/Trausan-Matu_et_al_2014_Intelligent_Tutoring_Systems.pdf:application/pdf},
}
@article{dillenbourg_framework_1992,
title = {A {Framework} for {Learner} {Modelling}},
volume = {2},
issn = {1049-4820, 1744-5191},
url = {http://www.tandfonline.com/doi/abs/10.1080/1049482920020202},
doi = {10.1080/1049482920020202},
abstract = {This paper presents a comprehensive conceptual framework and notation for learner modelling in intelligent tutoring systems (ITS). The framework is based upon the computational distinction between behavior, behavioral knowledge, and conceptual knowledge (in a "vertical" dimension) and between the system, the learner, and the system's representation of the learner (in a "horizontal" dimension). All existing techniques for learner modelling are placed within this framework. Methods for establishing the search space for learner models and for carrying out the search process are reviewed. The framework makes clear where particular learner modelling techniques are focused and shows that they are often complementary since they address different parts of the framework.},
language = {en},
number = {2},
urldate = {2021-04-07},
journal = {Interactive Learning Environments},
author = {Dillenbourg, Pierre and Self, John},
month = jun,
year = {1992},
pages = {111--137},
annote = {Publisher: Routledge \_eprint: https://doi.org/10.1080/1049482920020202},
file = {Dillenbourg_Self_1992_A_Framework_for_Learner_Modelling.pdf:files/6039/Dillenbourg_Self_1992_A_Framework_for_Learner_Modelling.pdf:application/pdf;Dillenbourg_Self_1992_A_Framework_for_Learner_Modelling.pdf:files/6055/Dillenbourg_Self_1992_A_Framework_for_Learner_Modelling.pdf:application/pdf;Snapshot:files/6052/1049482920020202.html:text/html},
}
@inproceedings{ferreira_automatic_2016,
address = {San Jose, CA, USA},
title = {An {Automatic} and {Dynamic} {Student} {Modeling} {Approach} for {Adaptive} and {Intelligent} {Educational} {Systems} {Using} {Ontologies} and {Bayesian} {Networks}},
isbn = {978-1-5090-4459-7},
url = {http://ieeexplore.ieee.org/document/7814676/},
doi = {10.1109/ICTAI.2016.0116},
abstract = {Dynamic adaptation of educational content has been an important research topic. Therefore, in order for it to run effectively, student models that properly describe and monitor the cognitive state of students are needed. In this sense, this paper presents a hybrid student model approach that combines ontologies and Bayesian Networks to identify the knowledge of each student based on their characteristics and behavior while using an Adaptive Educational System. Experiments were performed with real student participants in a higher education course using an experimental prototype developed to verify the viability of the approach, which showed satisfactory results.},
language = {en},
urldate = {2021-04-06},
booktitle = {2016 {IEEE} 28th {International} {Conference} on {Tools} with {Artificial} {Intelligence} ({ICTAI})},
publisher = {IEEE},
author = {Ferreira, Hiran Nonato M. and Brant-Ribeiro, Taffarel and Araujo, Rafael D. and Dorca, Fabiano A. and Cattelan, Renan G.},
month = nov,
year = {2016},
keywords = {Semantics, Collaboration, Adaptation models, Bayes methods, Bayesian Networks, Context, Ontologies, Student Modeling, Adaptive Learning Systems},
pages = {738--745},
annote = {ISSN: 2375-0197},
file = {Ferreira_et_al_2016_An_Automatic_and_Dynamic_Student_Modeling_Approach_for_Adaptive_and_Intelligent.pdf:files/6059/Ferreira_et_al_2016_An_Automatic_and_Dynamic_Student_Modeling_Approach_for_Adaptive_and_Intelligent.pdf:application/pdf;IEEE Xplore Abstract Record:files/6050/7814676.html:text/html},
}
@book{nguyen-xuan_les_2021,
title = {Les mécanismes cognitifs de l'apprentissage},
isbn = {978-1-78405-715-2},
abstract = {Les mécanismes cognitifs de l'apprentissage présente des travaux de recherche expérimentale sur la question de l'acquisition de connaissances en psychologie cognitive. Ces travaux de recherche - initiés par des groupes de chercheurs en philosophie, psychologie, linguistique et intelligence artificielle - explorent les mécanismes d'apprentissage en considérant les humains comme des systèmes de traitement de l'information. Centré principalement sur des recherches menées en laboratoire, cet ouvrage comporte également un chapitre consacré aux recherches appliquées, dérivées directement des travaux de recherche fondamentale. La modélisation informatique des mécanismes d'apprentissage est présentée en fonction du concept « d'architecture cognitive ». Trois questions majeures concernant la « méthodologie », les « réalisations » et l'« évolution » dans le domaine de l'apprentissage sont également examinées.},
language = {fr},
author = {Nguyen-Xuan, Anh},
year = {2021},
note = {OCLC: 1239319636},
file = {Nguyen-Xuan_2021_Les_mecanismes_cognitifs_de_l'apprentissage.pdf:files/6063/Nguyen-Xuan_2021_Les_mecanismes_cognitifs_de_l'apprentissage.pdf:application/pdf},
}
@article{moerland_model-based_2020,
title = {Model-based {Reinforcement} {Learning}: {A} {Survey}},
shorttitle = {Model-based {Reinforcement} {Learning}},
url = {http://arxiv.org/abs/2006.16712},
abstract = {Sequential decision making, commonly formalized as Markov Decision Process (MDP) optimization, is a key challenge in artificial intelligence. Two key approaches to this problem are reinforcement learning (RL) and planning. This paper presents a survey of the integration of both fields, better known as model-based reinforcement learning. Model-based RL has two main steps. First, we systematically cover approaches to dynamics model learning, including challenges like dealing with stochasticity, uncertainty, partial observability, and temporal abstraction. Second, we present a systematic categorization of planning-learning integration, including aspects like: where to start planning, what budgets to allocate to planning and real data collection, how to plan, and how to integrate planning in the learning and acting loop. After these two key sections, we also discuss the potential benefits of model-based RL, like enhanced data efficiency, targeted exploration, and improved stability. Along the survey, we also draw connections to several related RL fields, like hierarchical RL and transfer, and other research disciplines, like behavioural psychology. Altogether, the survey presents a broad conceptual overview of planning-learning combinations for MDP optimization.},
urldate = {2020-11-25},
journal = {arXiv:2006.16712 [cs, stat]},
author = {Moerland, Thomas M. and Broekens, Joost and Jonker, Catholijn M.},
month = jul,
year = {2020},
note = {arXiv: 2006.16712},
keywords = {Statistics - Machine Learning, Artificial intelligence, Machine Learning},
file = {arXiv.org Snapshot:/user/vthierry/home/.zotero/zotero/fy9peq9c.default/zotero/storage/RXBKGRYB/2006.html:text/html;Moerland_et_al_2020_Model-based_Reinforcement_Learning.pdf:files/7111/Moerland_et_al_2020_Model-based_Reinforcement_Learning.pdf:application/pdf},
}
@book{bordini_programming_2007,
address = {Chichester, UK},
series = {Wiley {Series} in {Agent} {Technology}},
title = {Programming {Multi}-{Agent} {Systems} in {AgentSpeak} {usingJason}},
isbn = {978-0-470-06184-8 978-0-470-02900-8},
url = {http://doi.wiley.com/10.1002/9780470061848},
language = {en},
urldate = {2021-05-12},
publisher = {John Wiley \& Sons, Ltd},
author = {Bordini, Rafael H. and Hbner, Jomi Fred and Wooldridge, Michael},
editor = {Wooldridge, Michael},
month = oct,
year = {2007},
doi = {10.1002/9780470061848},
file = {Bordini_et_al_2007_Programming_Multi-Agent_Systems_in_AgentSpeak_usingJason.pdf:files/6339/Bordini_et_al_2007_Programming_Multi-Agent_Systems_in_AgentSpeak_usingJason.pdf:application/pdf},
}
@article{laird_soar_nodate,
title = {The {Soar} {User}’s {Manual} {Version} 9.6.0},
language = {en},
author = {Laird, John E and Congdon, Clare Bates and Assanie, Mazin and Derbinsky, Nate and Xu, Joseph},
pages = {313},
file = {Laird_et_al_The_Soar_User’s_Manual_Version_9.pdf:files/6337/Laird_et_al_The_Soar_User’s_Manual_Version_9.pdf:application/pdf},
}
@article{siedlecka_but_2016,
title = {But {I} {Was} {So} {Sure}! {Metacognitive} {Judgments} {Are} {Less} {Accurate} {Given} {Prospectively} than {Retrospectively}},
volume = {7},
issn = {1664-1078},
url = {https://www.frontiersin.org/articles/10.3389/fpsyg.2016.00218/full},
doi = {10.3389/fpsyg.2016.00218},
abstract = {Prospective and retrospective metacognitive judgments have been studied extensively in the field of memory however their accuracy has not been systematically compared. Such a comparison is important for studying how metacognitive judgments are formed. Here, we present the results of an experiment aiming to investigate the relation between performance in an anagram task and the accuracy of prospective and retrospective confidence judgments. Participants worked on anagrams and were then asked to respond whether a presented word was the solution. They also rated their confidence, either before or after the response and either before or after seeing the suggested solution. The results showed that although response accuracy always correlated with confidence, this relationship was weaker when metacognitive judgements were given before the response. We discuss the theoretical and methodological implications of this finding for studies on metacognition and consciousness.},
language = {English},
urldate = {2021-05-05},
journal = {Frontiers in Psychology},
author = {Siedlecka, Marta and Paulewicz, Borysław and Wierzchoń, Michał},
year = {2016},
note = {Publisher: Frontiers},
keywords = {Anagram task, Awareness, confidence ratings, Consciousness, Decision Making, metacognition, metacognitive awareness},
file = {Siedlecka_et_al_2016_But_I_Was_So_Sure.pdf:files/6340/Siedlecka_et_al_2016_But_I_Was_So_Sure.pdf:application/pdf},
}
@article{zawadzka_judgments_2015,
title = {Judgments of learning index relative confidence, not subjective probability},
volume = {43},
issn = {1532-5946},
url = {https://doi.org/10.3758/s13421-015-0532-4},
doi = {10.3758/s13421-015-0532-4},
abstract = {The underconfidence-with-practice (UWP) effect is a common finding in calibration studies concerned with judgments of learning (JOLs) elicited on a percentage scale. The UWP pattern is present when, in a procedure consisting of multiple study–test cycles, the mean scale JOLs underestimate the mean recall performance on Cycle 2 and beyond. Although this pattern is present both for items recalled and unrecalled on the preceding cycle, to date research has concentrated mostly on the sources of UWP for the latter type of items. In the present study, we aimed to bridge this gap. In three experiments, we examined calibration on the third of three cycles. The results of Experiment 1 demonstrated the typical pattern of higher recall and scale JOLs for previously recalled items than for unrecalled ones. More importantly, they also revealed that even though the UWP effect was found for items previously recalled both once and twice, its magnitude was greater for the former class of items. Experiments 2 and 3, which employed a binary betting task and a binary 0 \%/100 \% JOL task, respectively, demonstrated that people can accurately predict future recall for previously recalled items with binary decisions. In both experiments, the UWP effect was absent for both items recalled once and twice. We suggest that the sensitivity of scale JOLs, but not binary judgments, to the number of previous recall successes strengthens the claim of Hanczakowski, Zawadzka, Pasek, and Higham (Journal of Memory and Language 69:429–444, 2013) that scale JOLs reflect confidence in, rather than the subjective probability of, future recall.},
language = {en},
number = {8},
urldate = {2021-05-05},
journal = {Memory \& Cognition},
author = {Zawadzka, Katarzyna and Higham, Philip A.},
month = nov,
year = {2015},
pages = {1168--1179},
file = {Zawadzka_Higham_2015_Judgments_of_learning_index_relative_confidence,_not_subjective_probability.pdf:files/6341/Zawadzka_Higham_2015_Judgments_of_learning_index_relative_confidence,_not_subjective_probability.pdf:application/pdf},
}
@article{mcclelland_parallel_2003,
title = {The parallel distributed processing approach to semantic cognition},
volume = {4},
copyright = {2003 Nature Publishing Group},
issn = {1471-003X, 1471-0048},
url = {http://www.nature.com/articles/nrn1076},
doi = {10.1038/nrn1076},
abstract = {Semantic cognition encompasses human performance based on knowledge about the properties of objects, relations among objects and word meanings. One approach to semantic cognition has arisen within the parallel distributed processing (PDP) framework, in which cognitive processes arise from interactions of neurons through synaptic connections. The knowledge that governs processing is stored in the strengths of the connections and is acquired gradually through experience, simulating conceptual development in childhood. These ideas have been explored in a simulated neural network model that learns propositions about objects and their properties. The model is trained with propositions about several different plant and animal concepts, including trees, flowers, fish, birds and land animals. The model contains 'hidden' units between its inputs and outputs, over which it learns internal representations that capture semantic relationships between concepts. Learning is influenced by coherent covariation of properties — that is, by co-occurrence of the same ensemble of properties (has wings, has feathers, can fly) in a number of different items (in this case, all the birds). The model explains the tendency towards progressive differentiation of concepts observed in development and the reverse fine-to-coarse deterioration observed in a progressive neuropathological condition called semantic dementia. With appropriate assumptions about covariation of properties, and about the relative frequencies of concepts and of the words used to name them, the model also addresses many further findings in development, dementia and normal adult cognition. Like other, similarity-based theories, the model accounts for the influence of graded category membership on semantic task performance, and for frequency and typicality effects. It also provides a means of addressing some of the criticisms of these other theories. Specifically, it indicates how some properties of objects, including causal properties, come to be more important than other properties; why some groups of items seem to form natural or coherent categories; how domain-specific patterns of generalization and differentiation might arise; and how conceptual knowledge structures might reorganize over the course of development. The PDP approach might provide a mechanistic framework that can address many of the phenomena emphasized in an alternative approach based on naive domain theories specifying causal relations between objects and their properties. Some of the relevant phenomena have yet to be addressed by PDP models, leaving this as a task for the future.},
language = {en},
number = {4},
urldate = {2021-04-29},
journal = {Nature Reviews Neuroscience},
author = {McClelland, James L. and Rogers, Timothy T.},
month = apr,
year = {2003},
pages = {310--322},
file = {McClelland_Rogers_2003_The_parallel_distributed_processing_approach_to_semantic_cognition.pdf:files/6343/McClelland_Rogers_2003_The_parallel_distributed_processing_approach_to_semantic_cognition.pdf:application/pdf;Snapshot:files/6841/nrn1076.html:text/html},
}
@article{lengyel_hippocampal_nodate,
title = {Hippocampal {Contributions} to {Control}: {The} {Third} {Way}},
abstract = {Recent experimental studies have focused on the specialization of different neural structures for different types of instrumental behavior. Recent theoretical work has provided normative accounts for why there should be more than one control system, and how the output of different controllers can be integrated. Two particlar controllers have been identified, one associated with a forward model and the prefrontal cortex and a second associated with computationally simpler, habitual, actor-critic methods and part of the striatum. We argue here for the normative appropriateness of an additional, but so far marginalized control system, associated with episodic memory, and involving the hippocampus and medial temporal cortices. We analyze in depth a class of simple environments to show that episodic control should be useful in a range of cases characterized by complexity and inferential noise, and most particularly at the very early stages of learning, long before habitization has set in. We interpret data on the transfer of control from the hippocampus to the striatum in the light of this hypothesis.},
language = {en},
author = {Lengyel, Máté and Dayan, Peter},
pages = {8},
file = {Lengyel_Dayan_Hippocampal_Contributions_to_Control.pdf:files/6347/Lengyel_Dayan_Hippocampal_Contributions_to_Control.pdf:application/pdf},
}
@article{gershman_reinforcement_2017,
title = {Reinforcement {Learning} and {Episodic} {Memory} in {Humans} and {Animals}: {An} {Integrative} {Framework}},
volume = {68},
issn = {0066-4308, 1545-2085},
shorttitle = {Reinforcement {Learning} and {Episodic} {Memory} in {Humans} and {Animals}},
url = {http://www.annualreviews.org/doi/10.1146/annurev-psych-122414-033625},
doi = {10.1146/annurev-psych-122414-033625},
abstract = {We review the psychology and neuroscience of reinforcement learning (RL), which has experienced significant progress in the past two decades, enabled by the comprehensive experimental study of simple learning and decisionmaking tasks. However, one challenge in the study of RL is computational: The simplicity of these tasks ignores important aspects of reinforcement learning in the real world: (a) State spaces are high-dimensional, continuous, and partially observable; this implies that (b) data are relatively sparse and, indeed, precisely the same situation may never be encountered twice; furthermore, (c) rewards depend on the long-term consequences of actions in ways that violate the classical assumptions that make RL tractable. A seemingly distinct challenge is that, cognitively, theories of RL have largely involved procedural and semantic memory, the way in which knowledge about action values or world models extracted gradually from many experiences can drive choice. This focus on semantic memory leaves out many aspects of memory, such as episodic memory, related to the traces of individual events. We suggest that these two challenges are related. The computational challenge can be dealt with, in part, by endowing RL systems with episodic memory, allowing them to (a) efficiently approximate value functions over complex state spaces, (b) learn with very little data, and (c) bridge long-term dependencies between actions and rewards. We review the computational theory underlying this proposal and the empirical evidence to support it. Our proposal suggests that the ubiquitous and diverse roles of memory in RL may function as part of an integrated learning system.},
language = {en},
number = {1},
urldate = {2021-04-13},
journal = {Annual Review of Psychology},
author = {Gershman, Samuel J. and Daw, Nathaniel D.},
month = jan,
year = {2017},
pages = {101--128},
file = {Gershman_Daw_2017_Reinforcement_Learning_and_Episodic_Memory_in_Humans_and_Animals.pdf:files/7114/Gershman_Daw_2017_Reinforcement_Learning_and_Episodic_Memory_in_Humans_and_Animals.pdf:application/pdf;Reinforcement Learning and Episodic Memory in Humans and Animals\: An Integrative Framework | Annual Review of Psychology:files/6348/annurev-psych-122414-033625.html:text/html},
}
@article{collins_beyond_2020,
title = {Beyond simple dichotomies in reinforcement learning.},
volume = {21},
copyright = {2020 Springer Nature Limited},
issn = {1471-0048},
url = {https://www.nature.com/articles/s41583-020-0355-6},
doi = {10.1038/s41583-020-0355-6},
abstract = {Reinforcement learning (RL) is a framework of particular importance to psychology, neuroscience and machine learning. Interactions between these fields, as promoted through the common hub of RL, has facilitated paradigm shifts that relate multiple levels of analysis in a singular framework (for example, relating dopamine function to a computationally defined RL signal). Recently, more sophisticated RL algorithms have been proposed to better account for human learning, and in particular its oft-documented reliance on two separable systems: a model-based (MB) system and a model-free (MF) system. However, along with many benefits, this dichotomous lens can distort questions, and may contribute to an unnecessarily narrow perspective on learning and decision-making. Here, we outline some of the consequences that come from overconfidently mapping algorithms, such as MB versus MF RL, with putative cognitive processes. We argue that the field is well positioned to move beyond simplistic dichotomies, and we propose a means of refocusing research questions towards the rich and complex components that comprise learning and decision-making.},
language = {en},
number = {10},
urldate = {2021-04-21},
journal = {Nature Reviews Neuroscience},
author = {Collins, Anne G. E. and Cockburn, Jeffrey},
month = oct,
year = {2020},
note = {Number: 10
Publisher: Nature Publishing Group},
pages = {576--586},
file = {Collins_Cockburn_2020_Beyond simple dichotomies in reinforcement learning.pdf:files/7459/Collins_Cockburn_2020_Beyond simple dichotomies in reinforcement learning.pdf:application/pdf;Collins_Cockburn_2020_Beyond_dichotomies_in_reinforcement_learning.pdf:files/6350/Collins_Cockburn_2020_Beyond_dichotomies_in_reinforcement_learning.pdf:application/pdf;Snapshot:files/6351/s41583-020-0355-6.html:text/html},
}
@article{oreilly_goal-driven_2014,
title = {Goal-{Driven} {Cognition} in the {Brain}: {A} {Computational} {Framework}},
shorttitle = {Goal-{Driven} {Cognition} in the {Brain}},
url = {http://arxiv.org/abs/1404.7591},
abstract = {Current theoretical and computational models of dopamine-based reinforcement learning are largely rooted in the classical behaviorist tradition, and envision the organism as a purely reactive recipient of rewards and punishments, with resulting behavior that essentially reflects the sum of this reinforcement history. This framework is missing some fundamental features of the affective nervous system, most importantly, the central role of goals in driving and organizing behavior in a teleological manner. Even when goal-directed behaviors are considered in current frameworks, they are typically conceived of as arising in reaction to the environment, rather than being in place from the start. We hypothesize that goal-driven cognition is primary, and organized into two discrete phases: goal selection and goal engaged, which each have a substantially different effective value function. This dichotomy can potentially explain a wide range of phenomena, playing a central role in many clinical disorders, such as depression, OCD, ADHD, and PTSD, and providing a sensible account of the detailed biology and function of the dopamine system and larger limbic system, including critical ventral and medial prefrontal cortex. Computationally, reasoning backward from active goals to action selection is more tractable than projecting alternative action choices forward to compute possible outcomes. An explicit computational model of these brain areas and their function in this goal-driven framework is described, as are numerous testable predictions from this framework.},
urldate = {2021-04-21},
journal = {arXiv:1404.7591 [q-bio]},
author = {O'Reilly, Randall C. and Hazy, Thomas E. and Mollick, Jessica and Mackie, Prescott and Herd, Seth},
month = apr,
year = {2014},
note = {arXiv: 1404.7591},
keywords = {cognition, model, Quantitative Biology - Neurons and Cognition, goal-oriented},
annote = {Comment: 62 pages, 11 figures},
annote = {Goal-Driven cognition in the brain: A computational framework. arXiv.
cf also: http://books.google.fr/books?id=AizFN8A2SaMC\&pg=PA71\&lpg=PA71\&dq=Integrating+what++how/where+with+instrumental+and+pavlovian+learning:+a+biologically-based+computational+model\&source=bl\&ots=ny\_sElkuSG\&sig=-K7O1Fx-FDGlHaMe0gYU3eWe-ko\&hl=fr\&sa=X\&ei=\_0QZVMTTC8XuaJmIgLgE\&ved=0CCYQ6AEwAA\#v=onepage\&q=Integrating\%20what\%20\%20how\%2Fwhere\%20with\%20instrumental\%20and\%20pavlovian\%20learning\%3A\%20a\%20biologically-based\%20computational\%20model\&f=false
pre-print of Goal-Driven Cognition in the Brain: a Computational Framework OReillyHazyMollickEtAl14.pdf
Abstract: models of DA-based RL in behaviorist tradition: organism = reactive recipient of reward/punishments, behavior resulting from history. This framework misses affective nervous system, goals; teleogical view of organization of behavior. When goals are considered, arise in reaction to envt (and not internal goals). Here consider goal-driven cognition, organized in two phases: goal selection and goal engaged (each with different value function). Appli in clinical disorders; role of DA and limbic system (dont ventral et mPFC). Computationally, use reasoning backward from goals to actions more tractable than projecting actions to compute possible outcomes. Propose such a model.
Intro: Behaviorism: temporal models of causality: stimuli trigger actions leading to outcomes. Our experience: our goals (mental representations of desired states) determine actions.
In RL, S-R learning prominent: actions triggered by states of envt and lead to reinforcement and performed more frequently in similar states else attenuated: Thorndike's Law of Effect. cf also Model-free and model-based forms of RL Model-free = standard S-R-O; model-based use internal model to anticipate future outcomes in a sequence of actions: what-if analysis; new approach but becomes surprisingly quickly untractable Solway12 et teleogical approach based on goals remains more interesting.
This paper: biologically informed and constrained comput framework of cognition starting with goals. Main hypo: Y two states of mental life: goal selection and goal engaged with different value functions (because strong motivation to achieve one goal when selected). cf Pezzulo09.
Link with neuroscience of affective behavior and cognitive control: v/mPFC, including OFC, medial wall including ACC. Representation of hot goals in v/mPFC have an energizing influence on processing in the brain including on executive control in lPFC: selection and maintenance of cold goals or task set representations. Here focus on hot side.
Some principles:
Principle 1: Active goals are primary and at least one must be engaged at all times; need clear criterion for accomplishment and perceptual component to track progress toward the goal and an action of how to proceed. Goals can be nested and stacked and several are possible but one proximal and concrete dominate the sphere of cognition: one's current concerns.
The term goal denotes a distributed representation that links 3 components:
an affective meaningful outcome
stimulus representations for progress toward goal achievement
action plans toward achieving the outcome.
This for hot goals, different from cold and different from affective states (being hungry).
Principle 2: Once activated, progress toward goals drives incremental DA release and reinforces actions and subgoals toward these goal states. Progress includes estimated time to achievement, degree of uncertainty of achievement, perceptual distance to goal state. This gradual progress leads to steady delivery of DA. Csq: impossible to stop close to goal: many examples.
Principle 3: It is relatively hard to activate new goals: brain at its most perfectionistic in weighting costs and benefits at the goal selection phase. (Difficile de choisir mais qd c'est fait on ne change plus). Dissociation of the value system between goal selection and goal engaged.
Principle 4: Despite the positive bias evident during goal engagement stage, a more balanced estimation of value does accumulate. Qd pas bon, on continue de le faire qd même mais on s'en souvient p ne pas selectionner la prochaine fois.
Principle 5: Not all goals achievable and system poised to detect when to give up on a given goal. When persistent lack of progress, goal reevaluation (steady progress is needed). More easy to try alternative strategies in cold lPFC than abandon an affective goal (depressed when give up, disappointment; not for strategies).
Principle 6: Aversive goal is an oxymoron: all goals are fundamentally appetitive. In aversive situations, goals focus on ways to avoid or overcome.
Principle 7: Goal activation is graded and not everything is goal-driven. en parallel à goal en cours, on peut faire autre chose, en mode habits model free en particulier.
In summary, two phases of cognition: goal selection and goal engaged; goal selection is the prime directive. puis resolution, donc moments critiques at every juncture.
Overview of proposed computational framework:
Central questions addressed: how do goals gain control of central neuromodulatory brain areas projecting to the rest of the brain to control learning and other dynamics? How are new goals activated?
Elaboration de gdPVLV (gd = goal-driven). Primary values affectively relevant (and associated to certain brain areas); learned values to associate to perceptual inputs and measures of distance. cf fig 2, liste de affective states et corresponding concrete goal and PV outcome. PV goals in v/mPFC OFC and ACC et primary values in ventral striatum. cf aussi liste autres buts plus sociaux (faire partie du gpe, se faire comprendre, curiosité vers nvelle info, etc.).
Role OFC: encoding running estimates of progress toward desired goal outcomes (primary values PV). Role of ACC: processing costs associated to specific ways of pursuing different goals: representation of utility expected from each goal-state/action-plan pair (???).
Y hierarchical pyramid of goal processing areas in the brain: au sommet, v/mPFC et ventral striatum (pvlv), analog prelimbic and infralimbic existe dejà in rodents avec petite partie du prelimbic homologous of the vast lPFC in primates (Narayanan06); ds OFC et ACC, Y aussi mechanism of active maintenance et adaptive gating que ds lPFC et en plus privileged access to other limbic areas, useful for goal processing. Mechanisms du genre incremental updating, running average of reward, effort, temporal derivative of running averages, link to phasic and tonic signals.
Description de la decomposition en sub-goals avec role du parietal dans cette decomposition en action à partir de perceptual and motor representation.
Computational Model of Rat Foraging Behavior
Test avec virtual rat ds plus maze et outcomes sur chaque location (protein, water, sugar, vegetables) mais p chacun chance of experiencing resp bitter, sour, rotten representant possible negative costs, effort, etc. goal = exploration depending on deprivation to optimize utility.
Period of purely random exploration (??? realist??? mais aussi reflecting background developmental learning processes) for initial associations, Selon needs (type of lack), activate corresponding positive outcome representation in OFC (the PV that satisfy the needs), connected to the corresponding ACC action plan value representations, utility of approaching the corresponding place with action plan itself encoded in dlPFC, receiving from ACC; Aussi interconnecté avec OFC negative outcome neurons (ou correspondant à sub-genual ACC area 25 ?) p negative outcomes associated with these actions. Donc ACC action plan representations coordinate multiple different OFC value representations, organized according to the relevant outcomes associated with different actions. cf role cortical processing ds constaint satisfaction with excitation and inhibition (OReilly13 et 12) et role frontal en particulier (Snyder 10 et 11) ds la vue de boucle avec BG et active maintenance par direct pathway. Decrit aussi d'autres étapes p selection du but puis realisation et reward ds amyg.
Testable predictions of the model: VS activity concentrated at start and end of tasks; dorsal striatum tracks online action selection during task performance: VS provides the discrete WM updating signals for goal maintenance in OFC and ACC at the transition from goal selection to goal engagement and then again to desactivate goals upon goal achievement and enable a new round of goal selection. Dorsal striatum involved in selecting online action plans along the task.
Integration of reward and cost depends on ACC and connections with BLA and VS. cf Walton03 et Rudebeck06.
OFC-mediated goal progress signals important for sustaining goal engagement (but explicit sensory cues can also suffice). OFC = highest level of the LV goal-progress tracking system. Capable of active maintenance of estimates of progress even in the absence of sensory input (OFC lesion = impulsive choice).
OFC important for outcome-based action selection (eg outcome devaluation). ??? ou ds mPFC mais ici bien etabli ; voir frontiere ou continuité mPFC/OFC???
Value function dissociations between goal selection and goal engaged modes. Goal selection: conservative weighting of costs and benefits. Goal engaged: progress toward the goal.
gdPVLV
reframing of PVLV from the goal-first point of view. Natural landmarks for perceptual cues of the distance to the goal for the LV system (in CeM ???). LV = proba of goal PV achievement through learned connections with perceptual inputs. Décrit les equations correspondantes. cf Hazy10 for second version of PVLV. A revoir en détail. Pour le cas pain et dips, role de LatHabenula mais plutot pour des 'anti-goals' à éviter.
A Goal-Processing Pyramid in the Brain
Pyramid inverted with narrow aspect in subcortical areas for PV system. When particular motivational state engaged, subcortical region for processing the relevant PV are up-regulated (primitive form of attention). Sensory inputs previously associated with those PV (food location) will activate LV representations for approach behavior. This system remains engaged as long as hungry. cf Fig 8. Core (positive and negative) PV in resp LH and MH; Core LV (pos and neg) in CeM and CeC/L; Higher level (more differentiated) PV and LV in BLA projecting to CeA and connected to OFC for anticipatory PV in reaction to LV-cues. BLA also connected to VS for driving gating of OFC and other v/mPFC by VS. At the highest level, OFC and ACC connected to lower levels including BLA and VS. OFC and ACC for overall maps of goal (cf Fig 9). cf sous-régions de OFC et continuité entre mOFC et sgACC p positive/negative PV et à un extrême lOFC plutot p sensory values from the senses vers vlPFC et WM/control over sensory what et pgACC p motor-action specific values (effort) vers dlPFC et action plans. et au milieu rmPFC for episodic input from the hippocampus. Contrast OFC/ACC: cf Rushworth07, Rudebeck08 et autres ref.
From this map of goals, propose to associate stimulus-driven OFC areas to LV stimulus driven graded representations of progress toward goals; ACC for representing affective consequences of actions to shape the selection process.
Taxonomy of Primary Values: putting emotional and motivational states in a goal-centric perspective. Distinguish affective states (more general, diffuse: drive) and outcomes. Reiss04 proposes a list of 16 intrinsic motivations. cf details.
Discussion
Central idea that goals are primary and one must have an active goal engaged. Process of goal selection by careful weighting of costs/benefits; when selected and engaged, dominate the effective value function, biased toward rewarding progress toward the goal. Conservative value function during selection; optimistic goal-dominated value during goal engaged mode.
Models with goal-driven component often in the symbolic domain (refs Sun09; ACT-R). cf also model-based RL approaches with internal model (Daw05, Dayan09, Rangel10) for construction of a goal-space. cf also Solway12 for a bayesian approach for running internal model backwards, but pb of grounding in the real world: only the planning aspect and not complete goal-driven cognition.
Pezzulo09 relies on forward projection to anticipate outcomes (on ne le fait pas trop with goal-selection happening first): is this look-ahead process done by animals? even by humans? not clear.
Major issues: role lateralization p left-approach et right-avoidance ? mais reste des pbs p negative: fuir ds quelle direction? jusqu'où?
Decomposition in sub-goals as hierarchy of LV or second-order PV? role BLA? Learning beyond second-order is extremely limited (different de TD).
Difference strategies (le sujet ici) et tactiques (differentes manière d'arriver au même but) qui pourrait plutôt impliquer parietal et cerebellum. cf negative fb controller that minimize discrepency between goals and current perceptual inputs; alors que DA system has a strong positive fb RL dynamic (representations become stronger and more likely to be activated). Ds ce dernier cas, on construit une representation stable à réutiliser alors que ds le premier cas, on est plutôt sur flexibilité devant unpredictable disturbances, sans vraiment d'app.
Novel pb solving: the idea with goal selection first is that you 'see' the path to the solution first, including for some hard pb, breaking them in more tractable smaller pbs. How these strategies are learned?
Potential relevance to clinical disorders: MDD, OCD, ADHD.
cf role NE ds exploration/exploitation correspondant à chercher a new goal or sticking to the current goal.
??? OK p difference goal selection and goal engaged mais comment se fait exactement goal selection (pourquoi prime? quelle asymmetry?), besoin d'integrer cout, effort, etc. p faire selection (donc pas si rough que ça ?)
Daw05, Daw, N. D., Niv, Y., \& Dayan, P. (2005). Uncertainty-based competition between prefrontal and dorsolateral striatal systems for behavioral control. Nature Neuroscience, 8(12), 1704–1711.
Dayan09 Dayan, P. (2009). Goal-directed control and its antipodes. Neural Networks, 22(3), 213–219.
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},
file = {arXiv.org Snapshot:files/6353/1404.html:text/html;O'Reilly_et_al_2014_Goal-Driven_Cognition_in_the_Brain.pdf:files/6354/O'Reilly_et_al_2014_Goal-Driven_Cognition_in_the_Brain.pdf:application/pdf},
}
@article{grimm_closed_nodate,
title = {Closed {World} {Reasoning} in the {Semantic} {Web} through {Epistemic} {Operators}},
abstract = {The open world assumption makes OWL principally suitable to handle incomplete knowledge in Semantic Web scenarios, however, some scenarios desire closed world reasoning. Autoepistemic description logics allow to realise closed world reasoning in open world settings through epistemic operators. An extension of OWL by epistemic operators therefore allows for non-monotonic features known from closed world systems, such as default rules, integrity constraints or epistemic querying. These features can be beneficially applied in Semantic Web scenarios, where OWL lacks expressiveness.},
language = {en},
author = {Grimm, Stephan and Motik, Boris},
pages = {10},
file = {Grimm_Motik_Closed_World_Reasoning_in_the_Semantic_Web_through_Epistemic_Operators.pdf:files/6355/Grimm_Motik_Closed_World_Reasoning_in_the_Semantic_Web_through_Epistemic_Operators.pdf:application/pdf},
}
@book{masolo_wonderweb_2003,
title = {Wonderweb deliverable d18: {Ontology} library},
publisher = {Technical report, ISTC-CNR},
author = {Masolo, Claudio and Borgo, Stefano and Gangemi, Aldo and Guarino, Nicola and Oltramari, Alessandro},
year = {2003},
file = {Masolo_et_al_2003_Wonderweb_deliverable_d18.pdf:files/6364/Masolo_et_al_2003_Wonderweb_deliverable_d18.pdf:application/pdf},
}
@inproceedings{shi_neural_2020,
address = {New York, NY, USA},
series = {{CIKM} '20},
title = {Neural {Logic} {Reasoning}},
isbn = {978-1-4503-6859-9},
url = {https://doi.org/10.1145/3340531.3411949},
doi = {10.1145/3340531.3411949},
abstract = {Recent years have witnessed the success of deep neural networks in many research areas. The fundamental idea behind the design of most neural networks is to learn similarity patterns from data for prediction and inference, which lacks the ability of cognitive reasoning. However, the concrete ability of reasoning is critical to many theoretical and practical problems. On the other hand, traditional symbolic reasoning methods do well in making logical inference, but they are mostly hard rule-based reasoning, which limits their generalization ability to different tasks since difference tasks may require different rules. Both reasoning and generalization ability are important for prediction tasks such as recommender systems, where reasoning provides strong connection between user history and target items for accurate prediction, and generalization helps the model to draw a robust user portrait over noisy inputs. In this paper, we propose Logic-Integrated Neural Network (LINN) to integrate the power of deep learning and logic reasoning. LINN is a dynamic neural architecture that builds the computational graph according to input logical expressions. It learns basic logical operations such as AND, OR, NOT as neural modules, and conducts propositional logical reasoning through the network for inference. Experiments on theoretical task show that LINN achieves significant performance on solving logical equations and variables. Furthermore, we test our approach on the practical task of recommendation by formulating the task into a logical inference problem. Experiments show that LINN significantly outperforms state-of-the-art recommendation models in Top-K recommendation, which verifies the potential of LINN in practice.},
urldate = {2021-05-24},
booktitle = {Proceedings of the 29th {ACM} {International} {Conference} on {Information} \& {Knowledge} {Management}},
publisher = {Association for Computing Machinery},
author = {Shi, Shaoyun and Chen, Hanxiong and Ma, Weizhi and Mao, Jiaxin and Zhang, Min and Zhang, Yongfeng},
month = oct,
year = {2020},
keywords = {neural networks, cognitive AI, collaborative reasoning, machine learning, machine reasoning},
pages = {1365--1374},
}
@article{graves_neural_2014,
title = {Neural {Turing} {Machines}},
url = {http://arxiv.org/abs/1410.5401},
abstract = {We extend the capabilities of neural networks by coupling them to external memory resources, which they can interact with by attentional processes. The combined system is analogous to a Turing Machine or Von Neumann architecture but is differentiable end-to-end, allowing it to be efficiently trained with gradient descent. Preliminary results demonstrate that Neural Turing Machines can infer simple algorithms such as copying, sorting, and associative recall from input and output examples.},
urldate = {2021-05-24},
journal = {arXiv:1410.5401 [cs]},
author = {Graves, Alex and Wayne, Greg and Danihelka, Ivo},
month = dec,
year = {2014},
note = {arXiv: 1410.5401},
keywords = {Computer Science - Neural and Evolutionary Computing},
file = {arXiv.org Snapshot:files/6370/1410.html:text/html;Graves_et_al_2014_Neural_Turing_Machines.pdf:files/6369/Graves_et_al_2014_Neural_Turing_Machines.pdf:application/pdf},
}
@article{riegel_logical_2020,
title = {Logical {Neural} {Networks}},
url = {http://arxiv.org/abs/2006.13155},
abstract = {We propose a novel framework seamlessly providing key properties of both neural nets (learning) and symbolic logic (knowledge and reasoning). Every neuron has a meaning as a component of a formula in a weighted real-valued logic, yielding a highly intepretable disentangled representation. Inference is omnidirectional rather than focused on predefined target variables, and corresponds to logical reasoning, including classical first-order logic theorem proving as a special case. The model is end-to-end differentiable, and learning minimizes a novel loss function capturing logical contradiction, yielding resilience to inconsistent knowledge. It also enables the open-world assumption by maintaining bounds on truth values which can have probabilistic semantics, yielding resilience to incomplete knowledge.},
urldate = {2021-05-24},
journal = {arXiv:2006.13155 [cs]},
author = {Riegel, Ryan and Gray, Alexander and Luus, Francois and Khan, Naweed and Makondo, Ndivhuwo and Akhalwaya, Ismail Yunus and Qian, Haifeng and Fagin, Ronald and Barahona, Francisco and Sharma, Udit and Ikbal, Shajith and Karanam, Hima and Neelam, Sumit and Likhyani, Ankita and Srivastava, Santosh},
month = jun,
year = {2020},
note = {arXiv: 2006.13155},
keywords = {Artificial intelligence, Machine Learning, Logic},
annote = {Comment: 10 pages (incl. references), 38 pages supplementary, 7 figures, 9 tables, 6 algorithms. In submission to NeurIPS 2020},
file = {arXiv.org Snapshot:files/6374/2006.html:text/html;Riegel_et_al_2020_Logical_Neural_Networks.pdf:files/6596/Riegel_et_al_2020_Logical_Neural_Networks.pdf:application/pdf},
}
@article{garcez_neurosymbolic_2020,
title = {Neurosymbolic {AI}: {The} 3rd {Wave}},
shorttitle = {Neurosymbolic {AI}},
url = {http://arxiv.org/abs/2012.05876},
abstract = {Current advances in Artificial Intelligence (AI) and Machine Learning (ML) have achieved unprecedented impact across research communities and industry. Nevertheless, concerns about trust, safety, interpretability and accountability of AI were raised by influential thinkers. Many have identified the need for well-founded knowledge representation and reasoning to be integrated with deep learning and for sound explainability. Neural-symbolic computing has been an active area of research for many years seeking to bring together robust learning in neural networks with reasoning and explainability via symbolic representations for network models. In this paper, we relate recent and early research results in neurosymbolic AI with the objective of identifying the key ingredients of the next wave of AI systems. We focus on research that integrates in a principled way neural network-based learning with symbolic knowledge representation and logical reasoning. The insights provided by 20 years of neural-symbolic computing are shown to shed new light onto the increasingly prominent role of trust, safety, interpretability and accountability of AI. We also identify promising directions and challenges for the next decade of AI research from the perspective of neural-symbolic systems.},
language = {en},
urldate = {2021-05-26},
journal = {arXiv:2012.05876 [cs]},
author = {Garcez, Artur d'Avila and Lamb, Luis C.},
month = dec,
year = {2020},
note = {arXiv: 2012.05876},
keywords = {Artificial intelligence, I.2.6, I.2.4, Machine Learning},
annote = {Comment: 37 pages},
file = {Garcez_Lamb_2020_Neurosymbolic_AI.pdf:files/6377/Garcez_Lamb_2020_Neurosymbolic_AI.pdf:application/pdf},
}
@article{stancin_ontologies_2020,
title = {Ontologies in education – state of the art},
volume = {25},
issn = {1573-7608},
url = {https://doi.org/10.1007/s10639-020-10226-z},
doi = {10.1007/s10639-020-10226-z},
abstract = {Ontologies are used with great success in education because they allow to formulate the representation of a learning domain by specifying all concepts involved, relations between concepts and all properties and conditions that exist. The goal of this paper is to present the field of ontologies and give an overview of recent research in the field, in the context of education. As this paper presents a literature review, papers from the last five years were collected from the IEEE Xplore database, analysed and categorized based on the use of ontologies for: curriculum modelling and management, describing learning domains, learning data, and e-learning services. From the collected papers, a slightly growing trend in the contribution of ontologies to educational systems can be observed. Most studies used ontologies for describing learning domains, and some of the 95 collected papers could not fit in just one category because a system used more than one ontology. Throughout the work, the following contributions have been made: the term ontology was defined, the most common types of ontologies and commonly used methodologies for building ontologies were identified, and an overview of existing systems that use ontologies in the domain of education was given.},
language = {en},
number = {6},
urldate = {2021-05-31},
journal = {Education and Information Technologies},
author = {Stancin, Kristian and Poscic, Patrizia and Jaksic, Danijela},
month = nov,
year = {2020},
pages = {5301--5320},
file = {Stancin_et_al_2020_Ontologies_in_education_–_state_of_the_art.pdf:files/6450/Stancin_et_al_2020_Ontologies_in_education_–_state_of_the_art.pdf:application/pdf},
}
@article{george_review_2019,
title = {Review of ontology-based recommender systems in e-learning},
volume = {142},
issn = {0360-1315},
url = {https://www.sciencedirect.com/science/article/pii/S0360131519301952},
doi = {10.1016/j.compedu.2019.103642},
abstract = {In recent years there has been an enormous increase in learning resources available online through massive open online courses and learning management systems. In this context, personalized resource recommendation has become an even more significant challenge, thereby increasing research in that direction. Recommender systems use ontology, artificial intelligence, among other techniques to provide personalized recommendations. Ontology is a way to model learners and learning resources, among others, which helps to retrieve details. This, in turn, generates more relevant materials to learners. Ontologies have benefits of reusability, reasoning ability, and supports inference mechanisms, which helps to provide enhanced recommendations. The comprehensive survey in this paper gives an overview of the research in progress using ontology to achieve personalization in recommender systems in the e-learning domain.},
language = {en},
urldate = {2021-06-02},
journal = {Computers \& Education},
author = {George, Gina and Lal, Anisha M.},
month = dec,
year = {2019},
keywords = {Computer-mediated communication, Cooperative/collaborative learning, Human-computer interface, Intelligent tutoring systems},
pages = {103642},
file = {George_Lal_2019_Review_of_ontology-based_recommender_systems_in_e-learning.pdf:files/6430/George_Lal_2019_Review_of_ontology-based_recommender_systems_in_e-learning.pdf:application/pdf;ScienceDirect Snapshot:files/6381/S0360131519301952.html:text/html},
}
@article{nouira_ontology-based_2019,
title = {An ontology-based framework of assessment analytics for massive learning},
volume = {27},
copyright = {© 2019 Wiley Periodicals, Inc.},
issn = {1099-0542},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/cae.22155},
doi = {https://doi.org/10.1002/cae.22155},
abstract = {Analyzing learning traces is presently highly required in e-learning environment. Several communities have been developed to address this need, such as those of Learning Analytics and Educational Data Mining. The main step of performing a learning analytics process is the educational data collection. Actually, learning environments such as Massive Open Online Course (MOOC) generate a big amount of educational data. They can be divided into assessment data, collaboration data, communication data, and so on. When we focus on assessment, we can launch a new source of data that can be analyzed and hence contribute to the improvement of learning analytics field. In this paper, we explore, investigate and compare the set of learning analytics models in the literature. Then, we study them from assessment point of view. The only current learning analytics model which can support tracking and modeling assessment data is the xAPI data model. For this reason, we study and investigate the xAPI specification from assessment point of view. Based on identified weaknesses of xAPI specification, we propose an enhancement of its data model. This is to support the assessment analytics effectively. We present an ontological model for assessment analytics inspired from the xAPI specification. To validate our approach, we focus on massive learning traces extracted from a real MOOC. Thus, we define and execute the set of proposed steps of preprocessing stage that extracts assessment data from whole learning data. Furthermore, we develop a java semantic web application to convert assessment data extracted to OWL file according to our proposed ontological model for assessment analytics.},
language = {en},
number = {6},
urldate = {2021-06-02},
journal = {Computer Applications in Engineering Education},
author = {Nouira, Azer and Cheniti-Belcadhi, Lilia and Braham, Rafik},
year = {2019},
note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/cae.22155},
keywords = {ontology, assessment analytics, learning analytics, semantic web technologies},
pages = {1343--1360},
file = {Nouira_et_al_2019_An_ontology-based_framework_of_assessment_analytics_for_massive_learning.pdf:files/6384/Nouira_et_al_2019_An_ontology-based_framework_of_assessment_analytics_for_massive_learning.pdf:application/pdf;Snapshot:files/6385/cae.html:text/html},
}
@inproceedings{lebis_recherche_2019,
address = {Toulouse, France},
title = {Recherche intelligente de processus d'analyse de traces d'e-learning via des inférences sémantiques},
url = {https://hal.archives-ouvertes.fr/hal-02155496},
abstract = {Le partage et la réutilisation de processus d'analyse de traces d'apprentissage, ainsi que leur adaptation à des contextes différents, sont devenus des enjeux importants dans le domaine des Learning Analytics. L'objectif est double : impliquer et soutenir la communauté dans le cycle du processus d'analyse, de son élaboration à son utilisation, et lui donner les outils nécessaires pour promouvoir une co-construction de ces analyses. Dès lors, il apparaît important de fournir aux différents acteurs des outils pour les assis-ter dans leur tâche respective, au sein de l'analyse. Dans cet article, nous présentons une assistance à la réutilisation des processus d'analyse de traces d'apprentissage via une recherche exploitant la représentation sémantique de ces processus d'analyse.},
urldate = {2021-06-02},
booktitle = {Journées francophones d'{Ingénierie} des {Connaissances} ({IC})},
author = {Lebis, Alexis and Lefevre, Marie and Luengo, Vanda and Guin, Nathalie},
month = jul,
year = {2019},
keywords = {Assistance, Environnements Informatiques pour l'Apprentissage Humain (EIAH), Inférence, Narration, Ontologie, Processus d'analyse de traces d'apprentissage, Sémantique, Reasoning},
file = {Lebis_et_al_2019_Recherche_intelligente_de_processus_d'analyse_de_traces_d'e-learning_via_des.pdf:files/6388/Lebis_et_al_2019_Recherche_intelligente_de_processus_d'analyse_de_traces_d'e-learning_via_des.pdf:application/pdf},
}
@book{ness_knowledge_2007,
address = {Lanham, MD, US},
series = {Knowledge under construction: {The} importance of play in developing children's spatial and geometric thinking},
title = {Knowledge under construction: {The} importance of play in developing children's spatial and geometric thinking},
isbn = {978-0-7425-4789-6 978-0-7425-4788-9},
shorttitle = {Knowledge under construction},
abstract = {Knowledge under Construction investigates how young children develop spatial, geometric, and scientific thinking skills--particularly those associated with architecture. Based on original research and analysis of videotapes of children's play with blocks, the authors' findings suggest that such play is anything but pointless. Their conclusions fill in gaps in our current understanding of how children learn to think spatially and scientifically even while challenging portions of that understanding, including some of Piaget's thesis about the primacy of topological space in children's learning. A system of measurement developed to identify and categorize children's spontaneous behavior at play allows adults to observe patterns of behavior and record the development of process skills and cognitive abilities, enhancing our understanding of how children begin to learn about space and architectural relationships. The book also examines the educational implications of our enhanced understanding. One possible development is a new, alternative way to measure cognitive abilities and development in children based on their work with blocks. (PsycINFO Database Record (c) 2016 APA, all rights reserved)},
publisher = {Rowman \& Littlefield},
author = {Ness, Daniel and Farenga, Stephen J.},
year = {2007},
note = {Pages: xxiii, 257},
keywords = {Thinking, Cognitive Ability, Architecture, Childhood Play Behavior, Geometry, Piaget (Jean), Spatial Learning},
annote = {Knowledge under Construction investigates how young children develop spatial, geometric, and scientific thinking skills--particularly those associated with architecture. Based on original research and analysis of videotapes of children's play with blocks, the authors' findings suggest that such play is anything but pointless. Their conclusions fill in gaps in our current understanding of how children learn to think spatially and scientifically even while challenging portions of that understanding, including some of Piaget's thesis about the primacy of topological space in children's learning. A system of measurement developed to identify and categorize children's spontaneous behavior at play allows adults to observe patterns of behavior and record the development of process skills and cognitive abilities, enhancing our understanding of how children begin to learn about space and architectural relationships. The book also examines the educational implications of our enhanced understanding. One possible development is a new, alternative way to measure cognitive abilities and development in children based on their work with blocks.},
file = {Snapshot:files/6390/2007-05445-000.html:text/html},
}
@inproceedings{kalmpourtzis_artifactual_2020,
address = {Cham},
series = {Lecture {Notes} in {Computer} {Science}},
title = {Artifactual {Affordances} in {Playful} {Robotics}},
isbn = {978-3-030-63464-3},
doi = {10.1007/978-3-030-63464-3_30},
abstract = {Programmable toys present interesting tools for the creation and facilitation of learning experiences through gaming and robotics. In order though for educators and game designers to use these tools to their full potential and provide pedagogical opportunities to support problem-solving activities, we should identify and characterise artifactual affordances in playful robotics. In problem-solving activities, supported by educational robotics artifacts, learners need to identify the artifactual affordances through their interaction with the artifact. This study aims to identify artifactual affordances through the analysis of 15 participants’ engagement in the CreaCube task. In this playful problem-solving activity, based on the use of modular robotics, players need to manipulate and assemble robotic cubes in order to create independently moving vehicles. This study aims at providing an initial analysis for the study of artifactual affordances in playful educational robotics.},
language = {en},
booktitle = {International {Conference} on {Games} and {Learning} {Alliance}},
publisher = {Springer International Publishing},
author = {Kalmpourtzis, George and Romero, Margarida},
editor = {Marfisi-Schottman, Iza and Bellotti, Francesco and Hamon, Ludovic and Klemke, Roland},
year = {2020},
keywords = {Educational robotics, Game based learning, Human computer interaction, Affordance},
pages = {316--325},
file = {Kalmpourtzis_Romero_2020_Artifactual_Affordances_in_Playful_Robotics.pdf:files/7044/Kalmpourtzis_Romero_2020_Artifactual_Affordances_in_Playful_Robotics.pdf:application/pdf},
}
@article{leroy_interactivity_2021,
title = {Interactivity and materiality matter in creativity: educational robotics for the assessment of divergent thinking},
volume = {0},
issn = {1049-4820},
shorttitle = {Interactivity and materiality matter in creativity},
url = {https://doi.org/10.1080/10494820.2021.1875005},
doi = {10.1080/10494820.2021.1875005},
abstract = {Idea generation in interactive learning environments requires the consideration of the interactivity and materiality aspects of creativity. In educational robotics, idea generation is mediated through a technological object in a process allowing us to observe the three main components of divergent thinking: fluency, flexibility, and originality. Nevertheless, divergent thinking assessment has been mainly evaluated in the last decades through semantic idea generation tasks such the Alternative Uses Test (AUT), asking participants to write different uses for familiar objects. In our study, we aimed to analyze differences in the three divergent thinking components (fluency, flexibility, and originality) through the AUT as a semantic task and through an educational robotic task that engaged the participants in building their ideas interactively. Results show that the creative components are strongly correlated within but not between the two tasks, leading us to consider the differences in the creative processes engaged when generating ideas through building with robotic objects. The role of affordances in idea generation through educational robotics is discussed as an important difference to consider in the evaluation of creativity in interactive learning environments.},
number = {0},
urldate = {2021-06-03},
journal = {Interactive Learning Environments},
author = {Leroy, Anaïs and Romero, Margarida and Cassone, Laura},
month = jan,
year = {2021},
note = {Publisher: Routledge
\_eprint: https://doi.org/10.1080/10494820.2021.1875005},
keywords = {Creativity, divergent thinking, educational robotics, flexibility, fluency, originality},
pages = {1--12},
file = {Leroy_et_al_2021_Interactivity_and_materiality_matter_in_creativity.pdf:files/6398/Leroy_et_al_2021_Interactivity_and_materiality_matter_in_creativity.pdf:application/pdf;Snapshot:files/6399/10494820.2021.html:text/html},
}
@article{mcnerney_turtles_2004,
title = {From turtles to {Tangible} {Programming} {Bricks}: explorations in physical language design},
volume = {8},
issn = {1617-4917},
shorttitle = {From turtles to {Tangible} {Programming} {Bricks}},
url = {https://doi.org/10.1007/s00779-004-0295-6},
doi = {10.1007/s00779-004-0295-6},
abstract = {This article provides a historical overview of educational computing research at MIT from the mid-1960s to the present day, focusing on physical interfaces. It discusses some of the results of this research: electronic toys that help children develop advanced modes of thinking through free-form play. In this historical context, the article then describes and discusses the author’s own research into tangible programming, culminating in the development of the Tangible Programming Bricks system—a platform for creating microworlds for children to explore computation and scientific thinking.},
language = {en},
number = {5},
urldate = {2021-06-03},
journal = {Personal and Ubiquitous Computing},
author = {McNerney, Timothy S.},
month = sep,
year = {2004},
pages = {326--337},
}
@inproceedings{elfotouh_towards_2017,
address = {Cairo Egypt},
title = {Towards {A} {Comprehensive} {Serious} {Educational} {Games}' {Ontology}},
isbn = {978-1-4503-5512-4},
url = {https://dl.acm.org/doi/10.1145/3178298.3178304},
doi = {10.1145/3178298.3178304},
abstract = {Serious Educational Games (SEGs) are games that have a purpose that differs from those for entertainment only. SEGs offer learners practicing what they learnt. The analysis and design of such games require integrating game design activities with educational design concepts (such as learning objectives, assessment methods, and educational content design). In addition, the integration of these domains require interdisciplinary team. As a result, a clear, concise communication between team members is a difficult goal to achieve and ambiguity could arise. An ontology, as a domain modeling tool, could be used as a meta-model to guide a SEG design and the development team, in addition to bridging the communication gap between the game design and pedagogic domains. There is little proof that a comprehensive web-enabled SEGs’ ontology, which is characterized by completion, consistency, and reusability, exists. This paper presents our attempt to build a comprehensive web enabled SEGs ontology that could be exploited in the era of the semantic web to be shared and reused by the SEGs’ development community. It is available on Protégé.},
language = {en},
urldate = {2021-06-03},
booktitle = {Proceedings of the 3rd {Africa} and {Middle} {East} {Conference} on {Software} {Engineering}},
publisher = {ACM},
author = {Elfotouh, Ahmed M. Abou and Nasr, Eman S. and Gheith, Mervat H.},
month = dec,
year = {2017},
pages = {25--30},
file = {Elfotouh_et_al_2017_Towards_A_Comprehensive_Serious_Educational_Games'_Ontology.pdf:files/6429/Elfotouh_et_al_2017_Towards_A_Comprehensive_Serious_Educational_Games'_Ontology.pdf:application/pdf},
}
@misc{noauthor_ludo_nodate,
title = {The {Ludo} {Game} {Model} {Ontology} {Specification}},
url = {https://ns.inria.fr/ludo/v1/docs/gamemodel.html},
urldate = {2021-06-03},
file = {The Ludo Game Model Ontology Specification:files/6431/gamemodel.html:text/html},
}
@inproceedings{abou_elfotouh_serious_2017,
address = {Cham},
series = {Advances in {Intelligent} {Systems} and {Computing}},
title = {Serious {Educational} {Games}’ {Ontologies}: {A} {Survey} and {Comparison}},
isbn = {978-3-319-48308-5},
shorttitle = {Serious {Educational} {Games}’ {Ontologies}},
doi = {10.1007/978-3-319-48308-5_70},
abstract = {Serious Educational Games (SEGs) are games not having a mere purpose of entertainment. They benefit from the main characteristics of games, such as engagement and immersiveness to achieve pedagogic objectives. In spite of the promising results of SEGs reported in the literature, their analysis and design still require complex tasks that incorporate game design activities within an educational context. Ontologies that include concepts, relations, and governing rules for both games and education domains could offer an approach to solve such problem. An ontology, as a domain modeling tool, could be used as a meta-model to guide a SEG designer, in addition to bridging the communication gap between the game design and pedagogic domains. This paper presents a survey of available ontologies for SEGs in the literature, in addition to comparing them. We managed to find only two SEGs’ ontologies and a meta-model in the literature, and hence presented and compared them. After presenting the survey, and result analysis and general comparison, we followed an ontologies’ comparison method called OntoMetric for further evaluation of the current SEGs’ ontologies. Our research results revealed that SEGs’ ontologies in the literature have two main diverse perspectives. One perspective intensively focuses on the game domain concepts, and the other perspective focuses on the pedagogic domain concepts. In addition, there is little proof that a comprehensive web-based SEGs ontology, which is characterized by completion, consistency, and reusability exists.},
language = {en},
booktitle = {Proceedings of the {International} {Conference} on {Advanced} {Intelligent} {Systems} and {Informatics} 2016},
publisher = {Springer International Publishing},
author = {Abou Elfotouh, Ahmed M. and Nasr, Eman S. and Gheith, Mervat H.},
editor = {Hassanien, Aboul Ella and Shaalan, Khaled and Gaber, Tarek and Azar, Ahmad Taher and Tolba, M. F.},
year = {2017},
keywords = {Domain modeling, Model driven development, Ontology comparison, Serious educational games},
pages = {732--741},
file = {Abou_Elfotouh_et_al_2017_Serious_Educational_Games’_Ontologies.pdf:files/7115/Abou_Elfotouh_et_al_2017_Serious_Educational_Games’_Ontologies.pdf:application/pdf},
}
@inproceedings{conchinha_playful_2015,
address = {Setubal},
title = {Playful learning: {Educational} robotics applied to students with learning disabilities},
isbn = {978-1-5090-1435-4},
shorttitle = {Playful learning},
url = {http://ieeexplore.ieee.org/document/7451669/},
doi = {10.1109/SIIE.2015.7451669},
abstract = {Since the ratification of the Salamanca agreement in 1994 that it is the concern of schools to seek inclusive approaches that may lead all students to academic success through differentiated strategies and adaptations or curricular and environmental interventions, whenever necessary [1] [2].},
language = {en},
urldate = {2021-06-03},
booktitle = {2015 {International} {Symposium} on {Computers} in {Education} ({SIIE})},
publisher = {IEEE},
author = {Conchinha, Cristina and Osorio, Patricia and de Freitas, Joao Correia},
month = nov,
year = {2015},
pages = {167--171},
file = {Conchinha_et_al_2015_Playful_learning.pdf:files/6436/Conchinha_et_al_2015_Playful_learning.pdf:application/pdf;Snapshot:files/6435/Playful_learning_Educational_robotics_applied_to_students_with_learning_disabilities.html:text/html},
}
@article{schraw_cognitive_1995,
title = {Cognitive processes in well-defined and ill-defined problem solving},
volume = {9},
copyright = {Copyright © 1995 John Wiley \& Sons, Ltd},
issn = {1099-0720},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/acp.2350090605},
doi = {https://doi.org/10.1002/acp.2350090605},
abstract = {We investigated the relationship between two kinds of problem solving using Kitchener's model of hierarchical cognitive processing. We predicted that performance on well-defined problems (i. e. those with a single, guaranteed solution) would be independent of ill-defined problems (i. e. those with multiple, non-guaranteed solutions). We also predicted that self-reported epistemic beliefs (i. e. assumptions about the nature and acquisition of knowledge) would be related to ill-defined, but not well-defined, solutions. Results confirmed these predictions. We concluded that well-defined and ill-defined problems require separate cognitive processes and that epistemic beliefs play an important role in ill-defined problem solving. These findings supported Kitchener's three-level model of problem solving.},
language = {en},
number = {6},
urldate = {2021-06-03},
journal = {Applied Cognitive Psychology},
author = {Schraw, Gregory and Dunkle, Michael E. and Bendixen, Lisa D.},
year = {1995},
keywords = {Models, Problem Solving, Metacognition, Cognitive Processes},
pages = {523--538},
file = {Schraw_et_al_1995_Cognitive_processes_in_well-defined_and_ill-defined_problem_solving.pdf:files/6437/Schraw_et_al_1995_Cognitive_processes_in_well-defined_and_ill-defined_problem_solving.pdf:application/pdf;Snapshot:files/6404/1996-25255-001.html:text/html;Snapshot:files/6439/acp.html:text/html},
}
@article{jamone_affordances_2016,
title = {Affordances in {Psychology}, {Neuroscience}, and {Robotics}: {A} {Survey}},
volume = {10},
issn = {2379-8920, 2379-8939},
shorttitle = {Affordances in {Psychology}, {Neuroscience}, and {Robotics}},
url = {http://ieeexplore.ieee.org/document/7523298/},
doi = {10.1109/TCDS.2016.2594134},
abstract = {The concept of affordances appeared in psychology during the late 60’s as an alternative perspective on the visual perception of the environment. It was revolutionary in the intuition that the way living beings perceive the world is deeply influenced by the actions they are able to perform. Then, across the last 40 years, it has influenced many applied fields: e.g. design, human-computer interaction, computer vision, robotics. In this paper we offer a multidisciplinary perspective on the notion of affordances: we first discuss the main definitions and formalizations of the affordance theory, then we report the most significant evidence in psychology and neuroscience that support it, and finally we review the most relevant applications of this concept in robotics.},
language = {en},
number = {1},
urldate = {2021-06-03},
journal = {IEEE Transactions on Cognitive and Developmental Systems},
author = {Jamone, Lorenzo and Ugur, Emre and Cangelosi, Angelo and Fadiga, Luciano and Bernardino, Alexandre and Piater, Justus and Santos-Victor, Jose},
year = {2016},
pages = {4--25},
file = {Jamone_et_al_2016_Affordances_in_Psychology,_Neuroscience,_and_Robotics.pdf:files/6438/Jamone_et_al_2016_Affordances_in_Psychology,_Neuroscience,_and_Robotics.pdf:application/pdf},
}
@article{ness_blocks_2016,
title = {Blocks, {Bricks}, and {Planks}: {Relationships} between {Affordance} and {Visuo}-{Spatial} {Constructive} {Play} {Objects}},
volume = {8},
issn = {1938-0399},
shorttitle = {Blocks, {Bricks}, and {Planks}},
url = {https://eric.ed.gov/?id=EJ1096889},
abstract = {The authors consider the strengths and weaknesses of three different visuo-spatial constructive play object (VCPO) types--blocks, bricks, and planks--and their impact on the development of creativity in spatial thinking and higher learning during free play. Each VCPO has its own set of attributes, they note, leading to different purposes, functions, aesthetic outcomes, and narratives. They argue that one key to understanding the impact of these toys is to determine, based on the diversity of their attributes, each VCPO's level of affordance. The authors suggest that the specific qualities of some play materials may help establish the scientific, mathematical, and technological foundations required in such professional disciplines as architecture and engineering. In contrast, they argue that the use of VCPOs hobbled by formulaic, scripted play properties may have the opposite effect, that the use of products manufactured with specialized, commercialized themes runs the risk of impeding self-regulation and even creative ideation. They hope their findings serve as a starting point for future studies that examine the benefits and shortcomings of specific play objects on cognitive development and creativity.},
language = {en},
number = {2},
urldate = {2021-06-03},
journal = {American Journal of Play},
author = {Ness, Daniel and Farenga, Stephen J.},
year = {2016},
note = {Publisher: The Strong},
keywords = {Creative Thinking, Creativity, Thinking Skills, Teaching Methods, Play, Children, Cognitive Processes, Adults, Creativity Tests, Manipulative Materials, Spatial Ability, STEM Education, Visual Perception},
pages = {201--227},
file = {Ness_Farenga_2016_Blocks,_Bricks,_and_Planks.pdf:files/6440/Ness_Farenga_2016_Blocks,_Bricks,_and_Planks.pdf:application/pdf;Snapshot:files/6441/eric.ed.gov.html:text/html},
}
@misc{kalmpourtzis_definition_2020,
title = {A definition of educational games},
url = {https://georgekalmpourtzis.com/a-definition-of-educational-games/},
abstract = {If we examine different gaming definitions, we will observe that games are viewed as closed systems, the context of which has a meaning only inside their own scope. Johan Huizinga, proposed the notion of a playground, isolated from the real world, bound by specific rules, the rules of the game that someone plays. This playground […]},
language = {en-US},
urldate = {2021-06-03},
journal = {George Kalmpourtzis},
author = {Kalmpourtzis, George},
month = nov,
year = {2020},
}
@techreport{stocco_analysis_2019,
type = {preprint},
title = {Analysis of the {Human} {Connectome} {Data} {Supports} the {Notion} of {A} “{Common} {Model} of {Cognition}” for {Human} and {Human}-{Like} {Intelligence} {Across} {Domains}},
url = {http://biorxiv.org/lookup/doi/10.1101/703777},
abstract = {The Common Model of Cognition (CMC) is a consensus architecture for human and human-like artificial cognition. We hypothesized that, because of its generality, the CMC could be a candidate model of the large-scale functional architecture of the human brain. To this end, we analyzed neuroimaging from N=200 participants across seven tasks that cover the broad range of cognitive domains. The CMC framework was translated into a model of neural connectivity between brain regions homologous to CMC components. After the model was implemented and fitted using Dynamic Causal Modeling, its performance was compared against four alternative large-scale brain architectures that had been previously proposed in the field of neuroscience. The results show that the CMC outperforms the other four architectures within and across all domains. These findings suggest that a common, functional computational blueprint for human-like intelligence also captures the neural architecture that underpins human cognition.},
language = {en},
urldate = {2021-06-02},
institution = {Neuroscience},
author = {Stocco, Andrea and Sibert, Catherine and Steine-Hanson, Zoe and Koh, Natalie and Laird, John E. and Lebiere, Christian J. and Rosenbloom, Paul},
month = jul,
year = {2019},
doi = {10.1101/703777},
file = {Stocco_et_al_2019_Analysis_of_the_Human_Connectome_Data_Supports_the_Notion_of_A_“Common_Model_of.pdf:files/6445/Stocco_et_al_2019_Analysis_of_the_Human_Connectome_Data_Supports_the_Notion_of_A_“Common_Model_of.pdf:application/pdf},
}
@article{laird_standard_2017,
title = {A {Standard} {Model} of the {Mind}: {Toward} a {Common} {Computational} {Framework} across {Artificial} {Intelligence}, {Cognitive} {Science}, {Neuroscience}, and {Robotics}},
volume = {38},
issn = {2371-9621, 0738-4602},
shorttitle = {A {Standard} {Model} of the {Mind}},
url = {https://ojs.aaai.org/index.php/aimagazine/article/view/2744},
doi = {10.1609/aimag.v38i4.2744},
abstract = {The purpose of this article is to begin the process of engaging the international research community in developing what can be called a standard model of the mind, where the mind we have in mind here is human-like. The notion of a standard model has its roots in physics, where over more than a half-century the international community has developed and tested a standard model that combines much of what is known about particles. This model is assumed to be internally consistent, yet still have major gaps. Its function is to serve as a cumulative reference point for the field while also driving efforts to both extend and break it.},
language = {en},
number = {4},
urldate = {2021-06-02},
journal = {AI Magazine},
author = {Laird, John E. and Lebiere, Christian and Rosenbloom, Paul S.},
month = dec,
year = {2017},
pages = {13--26},
file = {Laird_et_al_2017_A_Standard_Model_of_the_Mind.pdf:files/6444/Laird_et_al_2017_A_Standard_Model_of_the_Mind.pdf:application/pdf},
}
@article{eastes_processus_nodate,
title = {Processus d'apprentissage, savoirs complexes et traitement de l'information: un modèle théorique à l'usage des praticiens, entre sciences cognitives, didactique et philosophie des sciences.},
language = {fr},
author = {Eastes, Richard-Emmanuel},
pages = {330},
file = {Eastes_Processus_d'apprentissage,_savoirs_complexes_et_traitement_de_l'information.pdf:files/6446/Eastes_Processus_d'apprentissage,_savoirs_complexes_et_traitement_de_l'information.pdf:application/pdf},
}
@article{ballard_deictic_1997,
title = {Deictic codes for the embodiment of cognition},
volume = {20},
issn = {0140-525X, 1469-1825},
url = {https://www.cambridge.org/core/product/identifier/S0140525X97001611/type/journal_article},
doi = {10.1017/S0140525X97001611},
abstract = {To describe phenomena that occur at different time scales, computational models of the brain must incorporate different levels of abstraction. At time scales of approximately 1⁄3 of a second, orienting movements of the body play a crucial role in cognition and form a useful computational level – more abstract than that used to capture natural phenomena but less abstract than what is traditionally used to study high-level cognitive processes such as reasoning. At this “embodiment level,” the constraints of the physical system determine the nature of cognitive operations. The key synergy is that at time scales of about 1⁄3 of a second, the natural sequentiality of body movements can be matched to the natural computational economies of sequential decision systems through a system of implicit reference called deictic in which pointing movements are used to bind objects in the world to cognitive programs. This target article focuses on how deictic bindings make it possible to perform natural tasks. Deictic computation provides a mechanism for representing the essential features that link external sensory data with internal cognitive programs and motor actions. One of the central features of cognition, working memory, can be related to moment-by-moment dispositions of body features such as eye movements and hand movements.},
language = {en},
number = {4},
urldate = {2021-06-02},
journal = {Behavioral and Brain Sciences},
author = {Ballard, Dana H. and Hayhoe, Mary M. and Pook, Polly K. and Rao, Rajesh P. N.},
month = dec,
year = {1997},
keywords = {Working memory, Affordance, Embodied cognition, Binding, Brain time scales, Deictic computations, Pointers, Sensory-motor tasks},
pages = {723--742},
annote = {Adress different time scales in brain processing
Deictic frames + pointers to make sense of the environment using contextual cues
could be useful to model affordances (ndlr)},
file = {Ballard_et_al_1997_Deictic_codes_for_the_embodiment_of_cognition.pdf:files/6447/Ballard_et_al_1997_Deictic_codes_for_the_embodiment_of_cognition.pdf:application/pdf},
}
@incollection{carbonell_using_1997,
address = {Berlin, Heidelberg},
title = {Using ontologies for defining tasks, problem-solving methods and their mappings},
volume = {1319},
isbn = {978-3-540-63592-5 978-3-540-69606-3},
url = {http://link.springer.com/10.1007/BFb0026781},
abstract = {In recent years two main technologies for knowledge sharing and reuse have emerged: ontologies and problem solving methods (PSMs). Ontologies specify reusable conceptualizations which can be shared by multiple reasoning components communicating during a problem solving process. PSMs describe in a domain-independent way the generic reasoning steps and knowledge types needed to perform a task. Typically PSMs are specified in a task-specific fashion, using modelling frameworks which describe their control and inference structures as well as their knowledge requirements and competence. In this paper we discuss a novel approach to PSM specification, which is based on the use of formal ontologies. In particular our specifications abstract from control, data flow and other dynamic aspects of PSMs to focus on the logical theory associated with a PSM (method ontology). This approach concentrates on the competence and knowledge requirements of a PSM, rather than internal control details, thus enabling black-box-style reuse. In the paper we also look at the nature of PSM specifications and we show that these can be characterised in a task-independent style as generic search strategies. The resulting 'modelling gap' between methodindependent task specifications and task-independent method ontologies can be bridged by constructing the relevant adapter ontology, which reformulates the method ontology in task-specific terms. An important aspect of the ontologycentred approach described here is that, in contrast with other characterisations of task-independent PSMs, it does away with the simple, binary distinction between weak and strong methods. We argue that any method can be defined in either taskindependent or task-dependent style and therefore such distinction is of limited utility in PSM reuse. The differences between PSMs which affect reuse concern the ontological commitments which they make with respect to domain knowledge and goal specifications.},
language = {en},
urldate = {2021-06-02},
booktitle = {Knowledge {Acquisition}, {Modeling} and {Management}},
publisher = {Springer Berlin Heidelberg},
author = {Fensel, D. and Motta, E. and Decker, S. and Zdrahal, Z.},
editor = {Carbonell, Jaime G. and Siekmann, Jörg and Goos, G. and Hartmanis, J. and van Leeuwen, J. and Plaza, Enric and Benjamins, Richard},
year = {1997},
doi = {10.1007/BFb0026781},
note = {Series Title: Lecture Notes in Computer Science},
pages = {113--128},
file = {Fensel_et_al_1997_Using_ontologies_for_defining_tasks,_problem-solving_methods_and_their_mappings.pdf:files/6448/Fensel_et_al_1997_Using_ontologies_for_defining_tasks,_problem-solving_methods_and_their_mappings.pdf:application/pdf},
}
@article{han_computational_2018,
title = {A computational tool for creative idea generation based on analogical reasoning and ontology},
volume = {32},
issn = {0890-0604, 1469-1760},
url = {https://www.cambridge.org/core/product/identifier/S0890060418000082/type/journal_article},
doi = {10.1017/S0890060418000082},
abstract = {Analogy is a core cognition process used to produce inferences as well as new ideas using previous knowledge and experience. Ontology is a formal representation of a set of domain concepts and their relationships. The use of analogy and ontology in design activities to support design creativity have previously been explored. This paper explores an approach to construct ontologies with sufficient richness and coverage to support reasoning over real-world datasets for prompting creative idea generation. This approach has been implemented into a computational tool for assisting designers in generating creative ideas during the early stages of design. The tool, called “the Retriever”, has been developed based on ontology by embracing the aspects of analogical reasoning. A case study has indicated that the tool can be effective and useful for idea generation. The results have indicated that the tool, in its current formulation, can significantly improve the fluency and flexibility of idea generation and the usefulness of ideas, as well as slightly increase the originality of ideas, for the case study concerned.},
language = {en},
number = {4},
urldate = {2021-06-01},
journal = {Artificial Intelligence for Engineering Design, Analysis and Manufacturing},
author = {Han, Ji and Shi, Feng and Chen, Liuqing and Childs, Peter R.N.},
month = nov,
year = {2018},
pages = {462--477},
file = {Han_et_al_2018_A_computational_tool_for_creative_idea_generation_based_on_analogical_reasoning.pdf:files/6449/Han_et_al_2018_A_computational_tool_for_creative_idea_generation_based_on_analogical_reasoning.pdf:application/pdf},
}
@article{dietrich_cognitive_2004,
title = {The cognitive neuroscience of creativity},
volume = {11},
issn = {1069-9384},
url = {http://link.springer.com/10.3758/BF03196731},
doi = {10.3758/bf03196731},
abstract = {This article outlines a framework of creativity based on functional neuroanatomy. Recent advances in the field of cognitive neuroscience have identified distinct brain circuits that are involved in specific higher brain functions. To date, these findings have not been applied to research on creativity. It is proposed that there are four basic types of creative insights, each mediated by a distinctive neural circuit. By definition, creative insights occur in consciousness. Given the view that the working memory buffer of the prefrontal cortex holds the content of consciousness, each of the four distinctive neural loops terminates there. When creativity is the result of deliberate control, as opposed to spontaneous generation, the prefrontal cortex also instigates the creative process. Both processing modes, deliberate and spontaneous, can guide neural computation in structures that contribute emotional content and in structures that provide cognitive analysis, yielding the four basic types of creativity. Supportive evidence from psychological, cognitive, and neuroscientific studies is presented and integrated in this article. The new theoretical framework systematizes the interaction between knowledge and creative thinking, and how the nature of this relationship changes as a function of domain and age. Implications for the arts and sciences are briefly discussed.},
language = {eng},
number = {6},
journal = {Psychonomic Bulletin \& Review},
author = {Dietrich, Arne},
month = dec,
year = {2004},
pmid = {15875970},
keywords = {Humans, Creativity, Cognition, Age Factors, Neurosciences},
pages = {1011--1026},
file = {Dietrich - 2004 - The cognitive neuroscience of creativity.pdf:files/6785/Dietrich - 2004 - The cognitive neuroscience of creativity.pdf:application/pdf;Dietrich - 2004 - The cognitive neuroscience of creativity.pdf:files/6786/Dietrich - 2004 - The cognitive neuroscience of creativity.pdf:application/pdf;Dietrich_2004_The_cognitive_neuroscience_of_creativity.pdf:files/6452/Dietrich_2004_The_cognitive_neuroscience_of_creativity.pdf:application/pdf},
}
@inproceedings{romero_analyzing_2019,
address = {Cham},
series = {Lecture {Notes} in {Computer} {Science}},
title = {Analyzing {Cognitive} {Flexibility} in {Older} {Adults} {Through} {Playing} with {Robotic} {Cubes}},
isbn = {978-3-030-22015-0},
doi = {10.1007/978-3-030-22015-0_42},
abstract = {Cognitive flexibility is an important ability to adapt to changing situations. We consider the evolution of technologies in the digital era as a changing situation requiring the individuals to maintain a certain cognitive flexibility. Across the lifespan, cognitive flexibility is an essential ability to adapt to a continuous evolution of human-computer interactions (HCI). In this study, we observe older adults in a playful robotic task aiming to observe their cognitive flexibility in order to consider if older adults shows an adequate level of cognitive flexibility to solve a problem solving task with unknown robotic cubes. The playful robotic task engages the participants individually in problem solving a puzzle-based challenge with modular robotics.},
language = {en},
booktitle = {Human {Aspects} of {IT} for the {Aged} {Population}. {Social} {Media}, {Games} and {Assistive} {Environments}},
publisher = {Springer International Publishing},
author = {Romero, Margarida},
editor = {Zhou, Jia and Salvendy, Gavriel},
year = {2019},
keywords = {Robotics, Cognitive flexibility, Human-computer interactions, Lifelong learning, Problem solving},
pages = {545--553},
file = {HAL Snapshot:files/6402/hal-02181080.html:text/html},
}
@article{pintrich_multiple_2000,
title = {Multiple goals, multiple pathways: {The} role of goal orientation in learning and achievement},
volume = {92},
issn = {1939-2176(Electronic),0022-0663(Print)},
shorttitle = {Multiple goals, multiple pathways},
doi = {10.1037/0022-0663.92.3.544},
abstract = {Mastery goals have been linked to adaptive outcomes in normative goal theory and research; performance goals, to less adaptive outcomes. In contrast, approach performance goals may be adaptive for some outcomes under a revised goal theory perspective. The current study addresses the role of multiple goals, both mastery and approach performance goals, and links them to multiple outcomes of motivation, affect, strategy use, and performance. Data were collected over 3 waves from 8th and 9th graders (N = 150) in their math classrooms using both self-report questionnaires and actual math grades. There was a general decline in adaptive outcomes over time, but these trends were moderated by the different patterns of multiple goals. In line with normative goal theory, mastery goals were adaptive; but also in line with the revised goal theory perspective, approach performance goals, when coupled with mastery goals, were just as adaptive. (PsycINFO Database Record (c) 2019 APA, all rights reserved)},
number = {3},
journal = {Journal of Educational Psychology},
author = {Pintrich, Paul R.},
year = {2000},
note = {Place: US
Publisher: American Psychological Association},
keywords = {Learning, Motivation, Emotions, Strategies, Goals, Academic Achievement, Cognitive Aging, Cognitive Strategies, Goal Orientation, Junior High School Students},
pages = {544--555},
file = {Pintrich_2000_Multiple_goals,_multiple_pathways.pdf:files/6463/Pintrich_2000_Multiple_goals,_multiple_pathways.pdf:application/pdf;Snapshot:files/6464/2000-12129-013.html:text/html},
}
@article{seijts_learning_2005,
title = {Learning versus performance goals: {When} should each be used?},
volume = {19},
number = {1},
journal = {Academy of Management Perspectives},
author = {Seijts, Gerard H and Latham, Gary P},
year = {2005},
note = {Publisher: Academy of Management Briarcliff Manor, NY 10510},
pages = {124--131},
}
@article{poortvliet_mastery_2016,
title = {Mastery {Goals}},
journal = {Encyclopedia of Personality and Individual Differences},
author = {Poortvliet, P Marijn},
year = {2016},
note = {Publisher: Springer},
pages = {1--4},
}
@article{milivojevic_insight_2015,
title = {Insight {Reconfigures} {Hippocampal}-{Prefrontal} {Memories}},
volume = {25},
issn = {09609822},
url = {https://linkinghub.elsevier.com/retrieve/pii/S0960982215000652},
doi = {10.1016/j.cub.2015.01.033},
abstract = {Our memories are remarkably dynamic and allow us to reinterpret the past once new information comes to light. Gaining novel insights can lead to mental reorganization of previously unrelated events, thus linking them into narratives. The hippocampus and medial prefrontal cortex (mPFC) support integration of partially overlapping events, but the neural mechanisms underlying the reorganization of memories for the formation of coherent narratives remain elusive. Here, we combine fMRI with The Sims 3 videos of life-like animated events, which could either be integrated into narratives or not. We show that insight triggers the emergence of de novo mnemonic representations of the narratives and is associated with increased neural similarity between linked event representations in the posterior hippocampus, mPFC, and autobiographical-memory network. Simultaneously, events irrelevant to the newly established memory of the narrative were pruned out. This process was accompanied by increased neural dissimilarity between non-linked event representations in the posterior hippocampus and mPFC and was additionally signaled by a mismatch response in the anterior hippocampus. Our results demonstrate that insight leads to neural reconfiguration of representational networks within a memory space and have implications for knowledge acquisition in educational settings.},
language = {en},
number = {7},
urldate = {2021-06-03},
journal = {Current Biology},
author = {Milivojevic, Branka and Vicente-Grabovetsky, Alejandro and Doeller, Christian F.},
month = mar,
year = {2015},
pages = {821--830},
file = {Milivojevic_et_al_2015_Insight_Reconfigures_Hippocampal-Prefrontal_Memories.pdf:files/6466/Milivojevic_et_al_2015_Insight_Reconfigures_Hippocampal-Prefrontal_Memories.pdf:application/pdf},
}
@article{noy_ontology_2001,
title = {Ontology {Development} 101: {A} {Guide} to {Creating} {Your} {First} {Ontology}},
shorttitle = {Ontology {Development} 101},
url = {/paper/Ontology-Development-101%3A-A-Guide-to-Creating-Your-Noy/c15cf32df98969af5eaf85ae3098df6d2180b637},
abstract = {1 Why develop an ontology? In recent years the development of ontologies—explicit formal specifications of the terms in the domain and relations among them (Gruber 1993)—has been moving from the realm of ArtificialIntelligence laboratories to the desktops of domain experts. Ontologies have become common on the World-Wide Web. The ontologies on the Web range from large taxonomies categorizing Web sites (such as on Yahoo!) to categorizations of products for sale and their features (such as on Amazon.com). The WWW Consortium (W3C) is developing the Resource Description Framework (Brickley and Guha 1999), a language for encoding knowledge on Web pages to make it understandable to electronic agents searching for information. The Defense Advanced Research Projects Agency (DARPA), in conjunction with the W3C, is developing DARPA Agent Markup Language (DAML) by extending RDF with more expressive constructs aimed at facilitating agent interaction on the Web (Hendler and McGuinness 2000). Many disciplines now develop standardized ontologies that domain experts can use to share and annotate information in their fields. Medicine, for example, has produced large, standardized, structured vocabularies such as SNOMED (Price and Spackman 2000) and the semantic network of the Unified Medical Language System (Humphreys and Lindberg 1993). Broad general-purpose ontologies are emerging as well. For example, the United Nations Development Program and Dun \& Bradstreet combined their efforts to develop the UNSPSC ontology which provides terminology for products and services (www.unspsc.org). An ontology defines a common vocabulary for researchers who need to share information in a domain. It includes machine-interpretable definitions of basic concepts in the domain and relations among them. Why would someone want to develop an ontology? Some of the reasons are:},
language = {en},
urldate = {2021-06-04},
journal = {undefined},
author = {Noy, Natasha},
year = {2001},
file = {Noy_2001_Ontology_Development_101.pdf:files/6474/Noy_2001_Ontology_Development_101.pdf:application/pdf;Snapshot:files/6473/c15cf32df98969af5eaf85ae3098df6d2180b637.html:text/html},
}
@inproceedings{fernandez-lopez_methontology_1997,
address = {Stanford University, EEUU},
title = {{METHONTOLOGY}: {From} {Ontological} {Art} {Towards} {Ontological} {Engineering}},
copyright = {(c) Editor/Autor},
shorttitle = {{METHONTOLOGY}},
url = {http://oa.upm.es/5484/},
abstract = {This paper does not pretend either to transform completely the ontological art in engineering or to enumerate exhaustively the complete set of works that has been reported in this area. Its goal is to clarify to readers interested in building ontologies from scratch, the activities they should perform and in which order, as well as the set of techniques to be used in each phase of the methodology. This paper only presents a set of activities that conform the ontology developmentp rocess, a life cycle to build ontologies based in evolving prototypes, and METHONTOLOGY, a well-structured methodology used to build ontologies from scratch. This paper gathers the experience of the authors on building an ontology in the domain of chemicals.},
language = {eng},
urldate = {2021-06-04},
booktitle = {Proceedings of the {Ontological} {Engineering} {AAAI}-97 {Spring} {Symposium} {Series}},
publisher = {Facultad de Informática (UPM)},
author = {Fernández-López, M. and Gómez-Pérez, A. and Juristo, N.},
month = mar,
year = {1997},
file = {Fernandez-Lopez_et_al_1997_METHONTOLOGY.pdf:files/6476/Fernandez-Lopez_et_al_1997_METHONTOLOGY.pdf:application/pdf;Snapshot:files/6475/5484.html:text/html},
}
@book{gibson_ecological_1979,
title = {The {Ecological} {Approach} to {Visual} {Perception}: {Classic} {Edition}},
isbn = {978-1-317-57938-0},
shorttitle = {The {Ecological} {Approach} to {Visual} {Perception}},
abstract = {This book, first published in 1979, is about how we see: the environment around us (its surfaces, their layout, and their colors and textures); where we are in the environment; whether or not we are moving and, if we are, where we are going; what things are good for; how to do things (to thread a needle or drive an automobile); or why things look as they do. The basic assumption is that vision depends on the eye which is connected to the brain. The author suggests that natural vision depends on the eyes in the head on a body supported by the ground, the brain being only the central organ of a complete visual system. When no constraints are put on the visual system, people look around, walk up to something interesting and move around it so as to see it from all sides, and go from one vista to another. That is natural vision -- and what this book is about.},
language = {en},
publisher = {Psychology Press},
author = {Gibson, James J.},
year = {1979},
note = {Google-Books-ID: 8BSLBQAAQBAJ},
keywords = {Psychology / Cognitive Psychology \& Cognition, Psychology / General, Psychology / Experimental Psychology},
}
@article{romero_metacognition_2004,
title = {Métacognition dans les {EIAH}},
journal = {Mémoire de DEA, LIUM, Université du Maine, Le Mans},
author = {Romero, Margarida},
month = jan,
year = {2004},
file = {Romero_2004_Metacognition_dans_les_EIAH.pdf:files/6501/Romero_2004_Metacognition_dans_les_EIAH.pdf:application/pdf},
}
@inproceedings{usart_impact_2011,
address = {Berlin, Heidelberg},
series = {Lecture {Notes} in {Computer} {Science}},
title = {Impact of the {Feeling} of {Knowledge} {Explicitness} in the {Learners}’ {Participation} and {Performance} in a {Collaborative} {Game} {Based} {Learning} {Activity}},
isbn = {978-3-642-23834-5},
doi = {10.1007/978-3-642-23834-5_3},
abstract = {Despite the growing interest in the Game Based Learning (GBL) literature (Squire, 2005; Gee, 2005), only a reduced number of studies have focused on the collaborative modality in GBL (Harteveld \& Bekebrede, 2011). Knowledge Group Awareness (KGA) designates the intersubjective perception of teammates’ knowledge. The use of especially designed gaming interfaces allows KGA declaration and displaying support by the introduction of the KGA explicitness systems, called by some authors KGA tools (Buder, 2010).This paper aims to study whether a structured explicitness of the KGA could play a core role in facilitating and improving collaborative face to face GBL performances. The KGA is operationalized through the Feeling of Knowledge (FOK) declaration. The FOK refers to the feelings a student has regarding his/her knowledge for a specific subject (Hart, 1965), it is defined by the student using a Confidence Level (CL) based in a 3 level scale. We expect that the FOK declaration process will have a positive impact in the learning process based in the GBL task, both in individual and collaborative phases of the GBL activity proposed to the students. However, we expect better performances in collaborative settings with the explicitness of the KGA thanks to the socially shared metacognition process, developed through the displaying of the intersubjective FOK. For this purpose we designed a collaborative SG in the field of finance, introducing an ad hoc KGA explicitness system with the aim of supporting the students’ FOK declaration according to the 3 CL. The first is analyzing the impact of the declaration of the FOK in individual performance when playing alone. The second one is analyzing the influence of shared visualization of the intersubjective FOK in the individual and collaborative performances, according to the symmetry of knowledge between dyad members. This environment permits researchers study different variables in order to study four hypotheses on learner’s performances and changes in their Feeling of knowledge (FOK) accuracies during collaborative game experience.},
language = {en},
booktitle = {Serious {Games} {Development} and {Applications}},
publisher = {Springer},
author = {Usart, Mireia and Romero, Margarida and Almirall, Esteve},
editor = {Ma, Minhua and Fradinho Oliveira, Manuel and Madeiras Pereira, João},
year = {2011},
keywords = {Collaborative Learning, Feeling of Knowledge, Finance, Game Based Learning, Knowledge Group Awareness tool, Management Game, Serious Game},
pages = {23--35},
}
@article{antes_effects_2009,
title = {Effects of {Time} {Frame} on {Creative} {Thought}: {Process} {Versus} {Problem}-{Solving} {Effects}},
volume = {21},
issn = {1040-0419, 1532-6934},
shorttitle = {Effects of {Time} {Frame} on {Creative} {Thought}},
url = {http://www.tandfonline.com/doi/abs/10.1080/10400410902855267},
doi = {10.1080/10400410902855267},
language = {en},
number = {2-3},
urldate = {2021-06-09},
journal = {Creativity Research Journal},
author = {Antes, Alison L. and Mumford, Michael D.},
month = may,
year = {2009},
pages = {166--182},
}
@article{besancon_evolution_2011,
title = {Évolution de l’évaluation de la créativité chez l’enfant de {Binet} à nos jours},
issn = {1969-0622, 1760-7760},
url = {http://journals.openedition.org/rechercheseducations/840},
doi = {10.4000/rechercheseducations.840},
number = {5},
urldate = {2021-06-09},
journal = {Recherches \& éducations},
author = {Besançon, Maud and Barbot, Baptiste and Lubart, Todd},
month = oct,
year = {2011},
pages = {215--226},
file = {Besancon_et_al_2011_Evolution_de_l’evaluation_de_la_creativite_chez_l’enfant_de_Binet_a_nos_jours.pdf:files/6503/Besancon_et_al_2011_Evolution_de_l’evaluation_de_la_creativite_chez_l’enfant_de_Binet_a_nos_jours.pdf:application/pdf},
}
@book{parnes_guide_1977,
title = {Guide to creative action},
publisher = {MacMillan Publishing Company},
author = {Parnes, Sidney Jay and Noller, Ruth B and Biondi, Angelo Mario},
year = {1977},
}
@article{torrance_quiet_1989,
title = {A quiet revolution.},
journal = {The journal of creative behavior},
author = {Torrance, E Paul and Goff, Kathy},
year = {1989},
note = {Publisher: Creative Education Foundation},
}
@article{molnar_inductive_2013,
title = {Inductive reasoning, domain specific and complex problem solving: {Relations} and development},
volume = {9},
journal = {Thinking skills and Creativity},
author = {Molnár, Gyöngyvér and Greiff, Samuel and Csapó, Ben{\textbackslash}Ho},
year = {2013},
note = {Publisher: Elsevier},
pages = {35--45},
}
@article{deblois_lenseignement_2016,
title = {L’enseignement ayant comme visée la compétence à résoudre des problèmes mathématiques: quels enjeux?},
volume = {44},
number = {2},
journal = {Éducation et francophonie},
author = {DeBlois, Lucie and Barma, Sylvie and Lavallée, Simon},
year = {2016},
note = {Publisher: Association canadienne d’éducation de langue française},
pages = {40--67},
}
@book{kilpatrick_adding_2002,
title = {Adding it up: {Helping} children learn mathematics},
publisher = {Citeseer},
author = {Kilpatrick, Jeremy and Swafford, Jane and Findell, Bradford},
year = {2002},
}
@article{guarino_bfo_2017,
title = {{BFO} and {DOLCE}: {So} {Far}, {So} {Close}...},
volume = {4},
language = {en},
number = {4},
author = {Guarino, Nicola},
year = {2017},
pages = {9},
file = {Guarino_2017_BFO_and_DOLCE.pdf:files/6504/Guarino_2017_BFO_and_DOLCE.pdf:application/pdf},
}
@article{hoekstra_ontology_2009,
title = {Ontology {Representation} - {Design} {Patterns} and {Ontologies} that {Make} {Sense}},
doi = {10.3233/978-1-60750-013-1-i},
abstract = {As the (in)famous definition states: 'An ontology is an explicit specification of a conceptualization'. However, an ontology is also a philosophical theory of existence, a knowledge management resource, a database schema, or a type of knowledge representation artefact on the semantic web. Over the years the term 'ontology' has been used in so many different ways that one can no longer be sure what is meant by it at any given occasion. This book clarifies the role ontologies play in knowledge representation; it discusses the distinctions with their use in philosophy, gives insight in the features, rationale and limitations of the OWL 2 web ontology language, and provides a critical review of methodologies and design principles advocated to improve the quality of ontologies. It covers both theory and practice of knowledge acquisition, representation and ontologies; it emphasises human understanding as knowledge structuring principle, and demonstrates this approach in the development of a core ontology of basic legal concepts (LKIF Core) and in the exploration of expressive ontology design patterns for the representation of social reality, change and causation, actions and transactions. In doing so it contributes to a better understanding of the representation of ontologies; or rather, what it means to do ontology representation.},
journal = {Frontiers in Artificial Intelligence and Applications},
author = {Hoekstra, R.},
year = {2009},
note = {IOS Press is an international science, technical and medical publisher of high-quality books for academics, scientists, and professionals in all fields. Some of the areas we publish in: -Biomedicine -Oncology -Artificial intelligence -Databases and information systems -Maritime engineering -Nanotechnology -Geoengineering -All aspects of physics -E-governance -E-commerce -The knowledge economy -Urban studies -Arms control -Understanding and responding to terrorism -Medical informatics -Computer Sciences},
file = {Hoekstra_2009_Ontology_Representation_-_Design_Patterns_and_Ontologies_that_Make_Sense.pdf:files/6505/Hoekstra_2009_Ontology_Representation_-_Design_Patterns_and_Ontologies_that_Make_Sense.pdf:application/pdf},
}
@article{pahl_ontology_nodate,
title = {Ontology {Technology} for the {Development} and {Deployment} of {Learning} {Technology} {Systems} - a {Survey}},
abstract = {The World-Wide Web is undergoing dramatic changes at the moment. The Semantic Web is an initiative to bring meaning to the Web. The Semantic Web is based on ontology technology – a knowledge representation framework – at its core. We illustrate the importance of this evolutionary development. We survey five scenarios demonstrating different forms of applications of ontology technologies in the development and deployment of learning technology systems. Ontology technologies are highly useful to organise, personalise, and publish learning content and to discover, generate, and compose learning objects.},
language = {en},
author = {Pahl, Claus and Holohan, Edmond},
pages = {8},
file = {Pahl_Holohan_Ontology_Technology_for_the_Development_and_Deployment_of_Learning_Technology.pdf:files/6507/Pahl_Holohan_Ontology_Technology_for_the_Development_and_Deployment_of_Learning_Technology.pdf:application/pdf},
}
@inproceedings{tang_game_2011,
title = {Game {Content} {Model}: {An} {Ontology} for {Documenting} {Serious} {Game} {Design}},
shorttitle = {Game {Content} {Model}},
doi = {10.1109/DeSE.2011.68},
abstract = {Computer games is a form of real-time interactive software wrapped in creatively crafted media that offers game-players engaging, goal-directed play. Designing computer games requires adequate experience and great attention to detail to describe the rules, play and aesthetics that compose the interactive experience. For inexperienced game designers, formalised methods such as game design languages and game meta-models can provide a guide and language to produce a game design specification correct by design. This paper introduces a new game content model that can aid game designers document specification of game design.},
booktitle = {2011 {Developments} in {E}-systems {Engineering}},
author = {Tang, Stephen and Hanneghan, Martin},
month = dec,
year = {2011},
keywords = {Computers, Games, Ontologies, Game Design Languages, Game Modelling, Game-Based Learning, Graphical user interfaces, Model Driven Development, Object oriented modeling, Serious Games, Software, Computational modelling},
pages = {431--436},
file = {Snapshot:files/6510/6149971.html:text/html;Tang_Hanneghan_2011_Game_Content_Model.pdf:files/6433/Tang_Hanneghan_2011_Game_Content_Model.pdf:application/pdf},
}
@article{eriksson_task_1995,
title = {Task modeling with reusable problem-solving methods},
volume = {79},
issn = {0004-3702},
url = {https://www.sciencedirect.com/science/article/pii/0004370294000409},
doi = {10.1016/0004-3702(94)00040-9},
abstract = {Problem-solving methods for knowledge-based systems establish the behavior of such systems by defining the roles in which domain knowledge is used and the ordering of inferences. Developers can compose problem-solving methods that accomplish complex application tasks from primitive, reusable methods. The key steps in this development approach are task analysis, method selection (from a library), and method configuration. Protégé-ii is a knowledge-engineering environment that allows developers to select and configure problem-solving methods. In addition, Protégé-ii generates domain-specific knowledge-acquisition tools that domain specialists can use to create knowledge bases on which the methods may operate. The board-game method is a problem-solving method that defines control knowledge for a class of tasks that developers can model in a highly specific way. The method adopts a conceptual model of problem solving in which the solution space is construed as a “game board” on which the problem solver moves “playing pieces” according to prespecified rules. This familiar conceptual model simplifies the developer's cognitive demands when configuring the board-game method to support new application tasks. We compare configuration of the board-game method to that of a chronological-backtracking problem-solving method for the same application tasks (for example, towers of Hanoi and the Sisyphus room-assignment problem). We also examine how method designers can specialize problem-solving methods by making ontological commitments to certain classes of tasks. We exemplify this technique by specializing the chronological-backtracking method to the board-game method.},
language = {en},
number = {2},
urldate = {2021-06-04},
journal = {Artificial Intelligence},
author = {Eriksson, Henrik and Shahar, Yuval and Tu, Samson W. and Puerta, Angel R. and Musen, Mark A.},
month = dec,
year = {1995},
pages = {293--326},
file = {Eriksson_et_al_1995_Task_modeling_with_reusable_problem-solving_methods.pdf:files/6512/Eriksson_et_al_1995_Task_modeling_with_reusable_problem-solving_methods.pdf:application/pdf;ScienceDirect Snapshot:files/6511/0004370294000409.html:text/html},
}
@article{creem_defining_2001,
series = {Beyond the decade of the brain: {Towards} functional neuronanatomy of the mind},
title = {Defining the cortical visual systems: “{What}”, “{Where}”, and “{How}”},
volume = {107},
issn = {0001-6918},
shorttitle = {Defining the cortical visual systems},
url = {https://www.sciencedirect.com/science/article/pii/S000169180100021X},
doi = {10.1016/S0001-6918(01)00021-X},
abstract = {The visual system historically has been defined as consisting of at least two broad subsystems subserving object and spatial vision. These visual processing streams have been organized both structurally as two distinct pathways in the brain, and functionally for the types of tasks that they mediate. The classic definition by Ungerleider and Mishkin labeled a ventral “what” stream to process object information and a dorsal “where” stream to process spatial information. More recently, Goodale and Milner redefined the two visual systems with a focus on the different ways in which visual information is transformed for different goals. They relabeled the dorsal stream as a “how” system for transforming visual information using an egocentric frame of reference in preparation for direct action. This paper reviews recent research from psychophysics, neurophysiology, neuropsychology and neuroimaging to define the roles of the ventral and dorsal visual processing streams. We discuss a possible solution that allows for both “where” and “how” systems that are functionally and structurally organized within the posterior parietal lobe.},
language = {en},
number = {1},
urldate = {2021-06-25},
journal = {Acta Psychologica},
author = {Creem, Sarah H and Proffitt, Dennis R},
month = apr,
year = {2001},
keywords = {Cognitive neuroscience, Parietal lobe, Perception and action, Spatial processing, Visual processing, Visuomotor system},
pages = {43--68},
file = {ScienceDirect Snapshot:files/6514/S000169180100021X.html:text/html},
}
@article{milner_two_2008,
series = {Consciousness and {Perception}: {Insights} and {Hindsights}},
title = {Two visual systems re-viewed},
volume = {46},
issn = {0028-3932},
url = {https://www.sciencedirect.com/science/article/pii/S0028393207003545},
doi = {10.1016/j.neuropsychologia.2007.10.005},
abstract = {The model proposed by the authors of two cortical systems providing ‘vision for action’ and ‘vision for perception’, respectively, owed much to the inspiration of Larry Weiskrantz. In the present article some essential concepts inherent in the model are summarized, and certain clarifications and refinements are offered. Some illustrations are given of recent experiments by ourselves and others that have prompted us to sharpen these concepts. Our explicit hope in writing our book in 1995 was to provide a theoretical framework that would stimulate research in the field. Conversely, well-designed empirical contributions conceived within the framework of the model are the only way for us to progress along the route towards a fully fleshed-out specification of its workings.},
language = {en},
number = {3},
urldate = {2021-06-25},
journal = {Neuropsychologia},
author = {Milner, A. D. and Goodale, M. A.},
month = jan,
year = {2008},
keywords = {Vision, Cortex, Dorsal stream, Perception, Ventral stream, Visuomotor control},
pages = {774--785},
file = {ScienceDirect Snapshot:files/6516/S0028393207003545.html:text/html},
}
@article{djebbara_sensorimotor_2019,
title = {Sensorimotor brain dynamics reflect architectural affordances},
volume = {116},
number = {29},
journal = {Proceedings of the National Academy of Sciences},
author = {Djebbara, Zakaria and Fich, Lars Brorson and Petrini, Laura and Gramann, Klaus},
month = jul,
year = {2019},
pages = {14769--14778},
file = {Sensorimotor brain dynamics reflect architectural affordances | PNAS:files/6518/14769.html:text/html},
}
@article{de_wit_affordances_2017,
title = {Affordances and neuroscience: {Steps} towards a successful marriage},
volume = {80},
issn = {1873-7528},
shorttitle = {Affordances and neuroscience},
doi = {10.1016/j.neubiorev.2017.07.008},
abstract = {The concept of affordance is rapidly gaining popularity in neuroscientific accounts of perception and action. This concept was introduced by James Gibson to refer to the action possibilities of the environment. By contrast, standard cognitive neuroscience typically uses the concept to refer to (action-oriented) representations in the brain. This paper will show that the view of affordances as representations firmly places the concept in the subject-object framework that dominates both psychology and neuroscience. Notably, Gibson introduced the affordance concept to overcome this very framework. We describe an account of the role of the brain in perception and action that is consistent with Gibson. Making use of neuroscientific findings of neural reuse, degeneracy and functional connectivity, we conceptualize neural regions in the brain as dispositional parts of perceptual and action systems that temporarily assemble to enable animals to directly perceive and - in the paradigmatic case - utilize the affordances of the environment.},
language = {eng},
journal = {Neuroscience and Biobehavioral Reviews},
author = {de Wit, Matthieu M. and de Vries, Simon and van der Kamp, John and Withagen, Rob},
month = sep,
year = {2017},
pmid = {28757455},
keywords = {Animals, Humans, Cognition, Models, Neurological, Perception, Action system, Affordance, Brain, Degeneracy, Functional connectivity, Gibson, Motor Activity, Neural reuse, Perceptual system, Standard cognitive neuroscience, Subject-object framework},
pages = {622--629},
}
@inproceedings{bhattacharyya_o-pro_2017,
address = {Cham},
series = {Lecture {Notes} in {Computer} {Science}},
title = {O-{PrO}: {An} {Ontology} for {Object} {Affordance} {Reasoning}},
isbn = {978-3-319-52503-7},
shorttitle = {O-{PrO}},
doi = {10.1007/978-3-319-52503-7_4},
abstract = {Object affordances provide useful information related to understanding of human activities. The aim of this paper is to create an ontology for object affordance reasoning that can be shared across different assistive robots operating within the household domain. A novel ontology called O-PrO (Object Property Ontology) consisting of 61 household objects is presented. The ontology can be used for computing cognitive and semantic object affordances.},
language = {en},
booktitle = {Intelligent {Human} {Computer} {Interaction}},
publisher = {Springer International Publishing},
author = {Bhattacharyya, Rupam and Bhuyan, Zubin and Hazarika, Shyamanta M.},
editor = {Basu, Anupam and Das, Sukhendu and Horain, Patrick and Bhattacharya, Samit},
year = {2017},
keywords = {Ontology, Assistive robot, Object affordance},
pages = {39--50},
file = {Bhattacharyya_et_al_2017_O-PrO.pdf:files/7037/Bhattacharyya_et_al_2017_O-PrO.pdf:application/pdf},
}
@article{serafini_logic_2016,
title = {Logic {Tensor} {Networks}: {Deep} {Learning} and {Logical} {Reasoning} from {Data} and {Knowledge}},
shorttitle = {Logic {Tensor} {Networks}},
url = {http://arxiv.org/abs/1606.04422},
abstract = {We propose Logic Tensor Networks: a uniform framework for integrating automatic learning and reasoning. A logic formalism called Real Logic is defined on a first-order language whereby formulas have truth-value in the interval [0,1] and semantics defined concretely on the domain of real numbers. Logical constants are interpreted as feature vectors of real numbers. Real Logic promotes a well-founded integration of deductive reasoning on a knowledge-base and efficient data-driven relational machine learning. We show how Real Logic can be implemented in deep Tensor Neural Networks with the use of Google's tensorflow primitives. The paper concludes with experiments applying Logic Tensor Networks on a simple but representative example of knowledge completion.},
urldate = {2021-07-20},
journal = {arXiv:1606.04422 [cs]},
author = {Serafini, Luciano and Garcez, Artur d'Avila},
month = jul,
year = {2016},
note = {arXiv: 1606.04422},
keywords = {Computer Science - Neural and Evolutionary Computing, Artificial intelligence, Machine Learning, Logic},
annote = {Comment: 12 pages, 2 figs, 1 table, 27 references},
file = {arXiv.org Snapshot:files/6540/1606.html:text/html;Serafini_Garcez_2016_Logic_Tensor_Networks.pdf:files/6539/Serafini_Garcez_2016_Logic_Tensor_Networks.pdf:application/pdf},
}
@inproceedings{lamb_connectionist_2007,
address = {Vancouver, British Columbia, Canada},
series = {{AAAI}'07},
title = {A connectionist cognitive model for temporal synchronisation and learning},
isbn = {978-1-57735-323-2},
abstract = {The importance of the efforts towards integrating the symbolic and connectionist paradigms of artificial intelligence has been widely recognised. Integration may lead to more effective and richer cognitive computational models, and to a better understanding of the processes of artificial intelligence across the field. This paper presents a new model for the representation, computation, and learning of temporal logic in connectionist systems. The model allows for the encoding of past and future temporal logic operators in neural networks, through a neural-symbolic translation algorithms introduced in the paper. The networks are relatively simple and can be used for reasoning about time and for learning by examples with the use of standard neural learning algorithms. We validate the model in a well-known application dealing WIth temporal synchronisation in distributed knowledge systems. This opens several interesting research paths in cognitive modelling, with potential applications in agent technology, learning and reasoning.},
urldate = {2021-07-20},
booktitle = {Proceedings of the 22nd national conference on {Artificial} intelligence - {Volume} 1},
publisher = {AAAI Press},
author = {Lamb, Luís C. and Borges, Rafael V. and d'Avila Garcez, Artur S.},
month = jul,
year = {2007},
pages = {827--832},
file = {A connectionist cognitive model for temporal synchronisation and learning | Proceedings of the 22nd national conference on Artificial intelligence - Volume 1:files/6542/1619645.html:text/html},
}
@article{besold_neural-symbolic_2017,
title = {Neural-{Symbolic} {Learning} and {Reasoning}: {A} {Survey} and {Interpretation}},
shorttitle = {Neural-{Symbolic} {Learning} and {Reasoning}},
url = {http://arxiv.org/abs/1711.03902},
abstract = {The study and understanding of human behaviour is relevant to computer science, artificial intelligence, neural computation, cognitive science, philosophy, psychology, and several other areas. Presupposing cognition as basis of behaviour, among the most prominent tools in the modelling of behaviour are computational-logic systems, connectionist models of cognition, and models of uncertainty. Recent studies in cognitive science, artificial intelligence, and psychology have produced a number of cognitive models of reasoning, learning, and language that are underpinned by computation. In addition, efforts in computer science research have led to the development of cognitive computational systems integrating machine learning and automated reasoning. Such systems have shown promise in a range of applications, including computational biology, fault diagnosis, training and assessment in simulators, and software verification. This joint survey reviews the personal ideas and views of several researchers on neural-symbolic learning and reasoning. The article is organised in three parts: Firstly, we frame the scope and goals of neural-symbolic computation and have a look at the theoretical foundations. We then proceed to describe the realisations of neural-symbolic computation, systems, and applications. Finally we present the challenges facing the area and avenues for further research.},
urldate = {2021-07-20},
journal = {arXiv:1711.03902 [cs]},
author = {Besold, Tarek R. and Garcez, Artur d'Avila and Bader, Sebastian and Bowman, Howard and Domingos, Pedro and Hitzler, Pascal and Kuehnberger, Kai-Uwe and Lamb, Luis C. and Lowd, Daniel and Lima, Priscila Machado Vieira and de Penning, Leo and Pinkas, Gadi and Poon, Hoifung and Zaverucha, Gerson},
month = nov,
year = {2017},
note = {arXiv: 1711.03902},
keywords = {Artificial intelligence},
annote = {Comment: 58 pages, work in progress},
file = {arXiv.org Snapshot:files/6547/1711.html:text/html;Besold_et_al_2017_Neural-Symbolic_Learning_and_Reasoning.pdf:files/6546/Besold_et_al_2017_Neural-Symbolic_Learning_and_Reasoning.pdf:application/pdf},
}
@article{cui_survey_2019,
title = {A {Survey} on {Network} {Embedding}},
volume = {31},
issn = {1558-2191},
doi = {10.1109/TKDE.2018.2849727},
abstract = {Network embedding assigns nodes in a network to low-dimensional representations and effectively preserves the network structure. Recently, a significant amount of progresses have been made toward this emerging network analysis paradigm. In this survey, we focus on categorizing and then reviewing the current development on network embedding methods, and point out its future research directions. We first summarize the motivation of network embedding. We discuss the classical graph embedding algorithms and their relationship with network embedding. Afterwards and primarily, we provide a comprehensive overview of a large number of network embedding methods in a systematic manner, covering the structure- and property-preserving network embedding methods, the network embedding methods with side information, and the advanced information preserving network embedding methods. Moreover, several evaluation approaches for network embedding and some useful online resources, including the network data sets and softwares, are reviewed, too. Finally, we discuss the framework of exploiting these network embedding methods to build an effective system and point out some potential future directions.},
number = {5},
journal = {IEEE Transactions on Knowledge and Data Engineering},
author = {Cui, Peng and Wang, Xiao and Pei, Jian and Zhu, Wenwu},
month = may,
year = {2019},
note = {Conference Name: IEEE Transactions on Knowledge and Data Engineering},
keywords = {Computational complexity, data science, Distributed databases, graph embedding, Image reconstruction, Machine learning, network analysis, Network embedding, Network topology, Social network services, Task analysis},
pages = {833--852},
file = {Cui_et_al_2019_A_Survey_on_Network_Embedding.pdf:files/6553/Cui_et_al_2019_A_Survey_on_Network_Embedding.pdf:application/pdf;IEEE Xplore Abstract Record:files/6552/8392745.html:text/html},
}
@book{xu_understanding_2020,
title = {Understanding graph embedding methods and their applications},
abstract = {Graph analytics can lead to better quantitative understanding and control of complex networks, but traditional methods suffer from high computational cost and excessive memory requirements associated with the high-dimensionality and heterogeneous characteristics of industrial size networks. Graph embedding techniques can be effective in converting high-dimensional sparse graphs into low-dimensional, dense and continuous vector spaces, preserving maximally the graph structure properties. Another type of emerging graph embedding employs Gaussian distribution-based graph embedding with important uncertainty estimation. The main goal of graph embedding methods is to pack every node's properties into a vector with a smaller dimension, hence, node similarity in the original complex irregular spaces can be easily quantified in the embedded vector spaces using standard metrics. The generated nonlinear and highly informative graph embeddings in the latent space can be conveniently used to address different downstream graph analytics tasks (e.g., node classification, link prediction, community detection, visualization, etc.). In this Review, we present some fundamental concepts in graph analytics and graph embedding methods, focusing in particular on random walk-based and neural network-based methods. We also discuss the emerging deep learning-based dynamic graph embedding methods. We highlight the distinct advantages of graph embedding methods in four diverse applications, and present implementation details and references to open-source software as well as available databases in the Appendix for the interested readers to start their exploration into graph analytics.},
author = {Xu, Mengjia},
month = dec,
year = {2020},
file = {Xu_2020_Understanding_graph_embedding_methods_and_their_applications.pdf:files/6555/Xu_2020_Understanding_graph_embedding_methods_and_their_applications.pdf:application/pdf},
}
@article{holt_two_2011,
chapter = {Books},
title = {Two {Brains} {Running}},
issn = {0362-4331},
url = {https://www.nytimes.com/2011/11/27/books/review/thinking-fast-and-slow-by-daniel-kahneman-book-review.html},
abstract = {In the conflict between intuitive and rational decision-making, which side wins?},
language = {en-US},
urldate = {2021-07-24},
journal = {The New York Times},
author = {Holt, Jim},
month = nov,
year = {2011},
keywords = {Books and Literature, Kahneman, Daniel},
file = {Snapshot:files/6558/thinking-fast-and-slow-by-daniel-kahneman-book-review.html:text/html},
}
@article{mikolov_efficient_2013,
title = {Efficient {Estimation} of {Word} {Representations} in {Vector} {Space}},
url = {http://arxiv.org/abs/1301.3781},
abstract = {We propose two novel model architectures for computing continuous vector representations of words from very large data sets. The quality of these representations is measured in a word similarity task, and the results are compared to the previously best performing techniques based on different types of neural networks. We observe large improvements in accuracy at much lower computational cost, i.e. it takes less than a day to learn high quality word vectors from a 1.6 billion words data set. Furthermore, we show that these vectors provide state-of-the-art performance on our test set for measuring syntactic and semantic word similarities.},
urldate = {2021-07-25},
journal = {arXiv:1301.3781 [cs]},
author = {Mikolov, Tomas and Chen, Kai and Corrado, Greg and Dean, Jeffrey},
month = sep,
year = {2013},
note = {arXiv: 1301.3781},
keywords = {Computation and Language},
file = {arXiv.org Snapshot:files/6561/1301.html:text/html;Mikolov_et_al_2013_Efficient_Estimation_of_Word_Representations_in_Vector_Space.pdf:files/6560/Mikolov_et_al_2013_Efficient_Estimation_of_Word_Representations_in_Vector_Space.pdf:application/pdf},
}
@misc{vieville_neurosym_2021,
title = {Neurosym - {Mnemosyne} team meeting},
url = {https://docs.google.com/presentation/d/189Q166S1h4TYCGbIdt-nGHtLRoqm-ZrEtyQ1w6zhAxc/edit?usp=drive_web&ouid=111495962261220832381&usp=embed_facebook},
language = {en},
urldate = {2021-07-28},
author = {Viéville, Thierry},
month = aug,
year = {2021},
file = {Snapshot:files/6598/edit.html:text/html},
}
@inproceedings{de_penning_neural-symbolic_2011,
address = {Barcelona, Catalonia, Spain},
series = {{IJCAI}'11},
title = {A {Neural}-{Symbolic} {Cognitive} {Agent} for {Online} {Learning} and {Reasoning}},
isbn = {978-1-57735-514-4},
abstract = {In real-world applications, the effective integration of learning and reasoning in a cognitive agent model is a difficult task. However, such integration may lead to a better understanding, use and construction of more realistic models. Unfortunately, existing models are either oversimplified or require much processing time, which is unsuitable for online learning and reasoning. Currently, controlled environments like training simulators do not effectively integrate learning and reasoning. In particular, higher-order concepts and cognitive abilities have many unknown temporal relations with the data, making it impossible to represent such relationships by hand. We introduce a novel cognitive agent model and architecture for online learning and reasoning that seeks to effectively represent, learn and reason in complex training environments. The agent architecture of the model combines neural learning with symbolic knowledge representation. It is capable of learning new hypotheses from observed data, and infer new beliefs based on these hypotheses. Furthermore, it deals with uncertainty and errors in the data using a Bayesian inference model. The validation of the model on real-time simulations and the results presented here indicate the promise of the approach when performing online learning and reasoning in real-world scenarios, with possible applications in a range of areas.},
urldate = {2021-07-28},
booktitle = {Proceedings of the {Twenty}-{Second} international joint conference on {Artificial} {Intelligence} - {Volume} {Volume} {Two}},
publisher = {AAAI Press},
author = {De Penning, H. L. H. and Garcez, A. S. D'Avila and Lamb, Luís C. and Meyer, John-Jules C.},
month = jul,
year = {2011},
pages = {1653--1658},
file = {De_Penning_et_al_2011_A_Neural-Symbolic_Cognitive_Agent_for_Online_Learning_and_Reasoning.pdf:files/6595/De_Penning_et_al_2011_A_Neural-Symbolic_Cognitive_Agent_for_Online_Learning_and_Reasoning.pdf:application/pdf},
}
@inproceedings{donadello_logic_2017,
address = {Melbourne, Australia},
title = {Logic {Tensor} {Networks} for {Semantic} {Image} {Interpretation}},
isbn = {978-0-9992411-0-3},
url = {https://www.ijcai.org/proceedings/2017/221},
doi = {10.24963/ijcai.2017/221},
abstract = {Semantic Image Interpretation (SII) is the task of extracting structured semantic descriptions from images. It is widely agreed that the combined use of visual data and background knowledge is of great importance for SII. Recently, Statistical Relational Learning (SRL) approaches have been developed for reasoning under uncertainty and learning in the presence of data and rich knowledge. Logic Tensor Networks (LTNs) are a SRL framework which integrates neural networks with first-order fuzzy logic to allow (i) efficient learning from noisy data in the presence of logical constraints, and (ii) reasoning with logical formulas describing general properties of the data. In this paper, we develop and apply LTNs to two of the main tasks of SII, namely, the classification of an image’s bounding boxes and the detection of the relevant part-of relations between objects. To the best of our knowledge, this is the first successful application of SRL to such SII tasks. The proposed approach is evaluated on a standard image processing benchmark. Experiments show that background knowledge in the form of logical constraints can improve the performance of purely data-driven approaches, including the state-of-theart Fast Region-based Convolutional Neural Networks (Fast R-CNN). Moreover, we show that the use of logical background knowledge adds robustness to the learning system when errors are present in the labels of the training data.},
language = {en},
urldate = {2021-07-28},
booktitle = {Proceedings of the {Twenty}-{Sixth} {International} {Joint} {Conference} on {Artificial} {Intelligence}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
author = {Donadello, Ivan and Serafini, Luciano and d'Avila Garcez, Artur},
month = aug,
year = {2017},
pages = {1596--1602},
file = {Donadello_et_al_2017_Logic_Tensor_Networks_for_Semantic_Image_Interpretation.pdf:files/6594/Donadello_et_al_2017_Logic_Tensor_Networks_for_Semantic_Image_Interpretation.pdf:application/pdf},
}
@article{badreddine_logic_2021,
title = {Logic {Tensor} {Networks}},
url = {http://arxiv.org/abs/2012.13635},
abstract = {Artificial Intelligence agents are required to learn from their surroundings and to reason about the knowledge that has been learned in order to make decisions. While state-of-the-art learning from data typically use sub-symbolic distributed representations, reasoning is normally useful at a higher level of abstraction with the use of a first-order logic language for knowledge representation. As a result, attempts at combining symbolic AI and neural computation into neural-symbolic systems have been on the increase. In this paper, we present Logic Tensor Networks (LTN), a neurosymbolic formalism and computational model that supports learning and reasoning through the introduction of a many-valued, end-to-end differentiable first-order logic called Real Logic as a representation language for deep learning. We show that LTN provides a uniform language for the specification and the computation of several AI tasks such as data clustering, multi-label classification, relational learning, query answering, semi-supervised learning, regression and embedding learning. We implement and illustrate each of the above tasks with a number of simple explanatory examples using TensorFlow 2. Keywords: Neurosymbolic AI, Deep Learning and Reasoning, Many-valued Logic.},
language = {en},
urldate = {2021-07-28},
journal = {arXiv:2012.13635 [cs]},
author = {Badreddine, Samy and Garcez, Artur d'Avila and Serafini, Luciano and Spranger, Michael},
month = jan,
year = {2021},
note = {arXiv: 2012.13635},
keywords = {Artificial intelligence, I.2.6, I.2.4, Machine Learning},
annote = {Comment: 68 pages, 28 figures, 6 tables},
file = {Badreddine_et_al_2021_Logic_Tensor_Networks.pdf:files/6593/Badreddine_et_al_2021_Logic_Tensor_Networks.pdf:application/pdf},
}
@article{oztop_schema_2002,
title = {Schema design and implementation of the grasp-related mirror neuron system},
volume = {87},
issn = {1432-0770},
url = {https://doi.org/10.1007/s00422-002-0318-1},
doi = {10.1007/s00422-002-0318-1},
abstract = {Mirror neurons within a monkey's premotor area F5 fire not only when the monkey performs a certain class of actions but also when the monkey observes another monkey (or the experimenter) perform a similar action. It has thus been argued that these neurons are crucial for understanding of actions by others. We offer the hand-state hypothesis as a new explanation of the evolution of this capability: the basic functionality of the F5 mirror system is to elaborate the appropriate feedback – what we call the hand state– for opposition-space based control of manual grasping of an object. Given this functionality, the social role of the F5 mirror system in understanding the actions of others may be seen as an exaptation gained by generalizing from one's own hand to an other's hand. In other words, mirror neurons first evolved to augment the “canonical” F5 neurons (active during self-movement based on observation of an object) by providing visual feedback on “hand state,” relating the shape of the hand to the shape of the object. We then introduce the MNS1 (mirror neuron system 1) model of F5 and related brain regions. The existing Fagg–Arbib–Rizzolatti–Sakata model represents circuitry for visually guided grasping of objects, linking the anterior intraparietal area (AIP) with F5 canonical neurons. The MNS1 model extends the AIP visual pathway by also modeling pathways, directed toward F5 mirror neurons, which match arm–hand trajectories to the affordances and location of a potential target object. We present the basic schemas for the MNS1 model, then aggregate them into three “grand schemas”– visual analysis of hand state, reach and grasp, and the core mirror circuit – for each of which we present a useful implementation (a non-neural visual processing system, a multijoint 3-D kinematics simulator, and a learning neural network, respectively). With this implementation we show how the mirror system may learnto recognize actions already in the repertoire of the F5 canonical neurons. We show that the connectivity pattern of mirror neuron circuitry can be established through training, and that the resultant network can exhibit a range of novel, physiologically interesting behaviors during the process of action recognition. We train the system on the basis of final grasp but then observe the whole time course of mirror neuron activity, yielding predictions for neurophysiological experiments under conditions of spatial perturbation, altered kinematics, and ambiguous grasp execution which highlight the importance of the timingof mirror neuron activity.},
language = {en},
number = {2},
urldate = {2021-06-25},
journal = {Biological Cybernetics},
author = {Oztop, Erhan and Arbib, Michael A.},
month = aug,
year = {2002},
pages = {116--140},
file = {Oztop_Arbib_2002_Schema_design_and_implementation_of_the_grasp-related_mirror_neuron_system.pdf:files/6603/Oztop_Arbib_2002_Schema_design_and_implementation_of_the_grasp-related_mirror_neuron_system.pdf:application/pdf},
}
@article{thill_theories_2013,
title = {Theories and computational models of affordance and mirror systems: {An} integrative review},
volume = {37},
issn = {0149-7634},
shorttitle = {Theories and computational models of affordance and mirror systems},
url = {https://www.sciencedirect.com/science/article/pii/S0149763413000134},
doi = {10.1016/j.neubiorev.2013.01.012},
abstract = {Neuroscientific and psychological data suggest a close link between affordance and mirror systems in the brain. However, we still lack a full understanding of both the individual systems and their interactions. Here, we propose that the architecture and functioning of the two systems is best understood in terms of two challenges faced by complex organisms, namely: (a) the need to select among multiple affordances and possible actions dependent on context and high-level goals and (b) the exploitation of the advantages deriving from a hierarchical organisation of behaviour based on actions and action-goals. We first review and analyse the psychological and neuroscientific literature on the mechanisms and processes organisms use to deal with these challenges. We then analyse existing computational models thereof. Finally we present the design of a computational framework that integrates the reviewed knowledge. The framework can be used both as a theoretical guidance to interpret empirical data and design new experiments, and to design computational models addressing specific problems debated in the literature.},
language = {en},
number = {3},
urldate = {2021-06-25},
journal = {Neuroscience \& Biobehavioral Reviews},
author = {Thill, Serge and Caligiore, Daniele and Borghi, Anna M. and Ziemke, Tom and Baldassarre, Gianluca},
month = mar,
year = {2013},
keywords = {Neuroscience, Psychology, Affordance processing, Canonical neurons, Computational modelling, Embodied cognition, Integration, Mirror system, Neurophysiology},
pages = {491--521},
file = {ScienceDirect Snapshot:files/6604/S0149763413000134.html:text/html;Thill_et_al_2013_Theories_and_computational_models_of_affordance_and_mirror_systems.pdf:files/6605/Thill_et_al_2013_Theories_and_computational_models_of_affordance_and_mirror_systems.pdf:application/pdf},
}
@article{sloman_possibility_2011,
title = {Possibility and {Necessity}},
language = {en},
author = {Sloman, Aaron},
year = {2011},
pages = {40},
file = {Sloman_2011_Possibility_and_Necessity.pdf:files/6709/Sloman_2011_Possibility_and_Necessity.pdf:application/pdf},
}
@article{taconnat_fonctionnement_2012,
title = {Fonctionnement et dysfonctionnement de la mémoire humaine},
volume = {297},
issn = {0752-501X, 2118-3015},
url = {http://www.cairn.info/revue-le-journal-des-psychologues-2012-4-page-18.htm},
doi = {10.3917/jdp.297.0018},
language = {fr},
number = {4},
urldate = {2021-06-22},
journal = {Le Journal des psychologues},
author = {Taconnat, Laurence},
year = {2012},
note = {Number: 4},
pages = {18},
file = {Taconnat_2012_Fonctionnement_et_dysfonctionnement_de_la_memoire_humaine.pdf:files/6711/Taconnat_2012_Fonctionnement_et_dysfonctionnement_de_la_memoire_humaine.pdf:application/pdf},
}
@article{blanchard-laville_co-disciplinarite_2000,
title = {De la co-disciplinarité en sciences de l'éducation},
url = {http://www.jstor.org/stable/41201594},
language = {fr},
number = {132,},
journal = {Revue française de pédagogie},
author = {Blanchard-Laville, Claudine},
year = {2000},
note = {Number: 132,},
pages = {55--66},
file = {Blanchard-Laville_2000_De_la_co-disciplinarite_en_sciences_de_l'education.pdf:files/6712/Blanchard-Laville_2000_De_la_co-disciplinarite_en_sciences_de_l'education.pdf:application/pdf},
}
@inproceedings{clement_online_2014,
title = {Online {Optimization} of {Teaching} {Sequences} with {Multi}-{Armed} {Bandits}},
url = {https://hal.inria.fr/hal-01016428},
abstract = {We present an approach to Intelligent Tutoring Systems which adaptively personalizes sequences of learning activities to maximize skills acquired by each student, taking into account limited time and motivational resources. At a given point in time, the system tries to propose to the student the activity which makes him progress best. We introduce two algorithms that rely on the empirical estimation of the learning progress, one that uses information about the difficulty of each exercise RiARiT and another that does not use any knowledge about the problem ZPDES.},
language = {en},
urldate = {2021-02-18},
author = {Clément, Benjamin and Roy, Didier and Oudeyer, Pierre-Yves and Lopes, Manuel},
year = {2014},
annote = {Extracted Annotations (12/10/2021, 7:08:04 PM)
"Intelligent Tutoring Systems (ITS) have been proposed to make education more accessible, more effective and simultaneously as a way to provide useful ob jective metrics on learning." (Clément, et and al 2014:2)
"In this work we are more focused on the tutoring model, that is, how to choose the activities that provide a better learning experience based on the estimation of the student competence levels and progression, and some knowledge about the cognitive and student model." (Clément, et and al 2014:2)
"A third approach, and more relevant for our work, is that the optimization is made automatically without particular assumptions about the students or the knowledge domain." (Clément, et and al 2014:2)
"Our ITS aims at providing to each particular student the activities that are giving the highest learning progress." (Clément, et and al 2014:2)
"ing on particular teaching activities; iii) a tutoring model that defines, based on the cognitive and the student model, what teaching activities to present to students and iv) a user interface model that represents how the interaction with the students occurs and how problems are proposed to the learners. According to [13], there are four main components of an ITS: i) a cognitive model that defines the domain knowledge or which steps need to be made to solve problems in a particular domain; ii) a student model that considers how students learn, what is the evolution of their cognitive state depend-" (Clément, et and al 2014:2)
A représenter avec un schéma (note on p.2)
"Weaker dependency on the cognitive/student model" (Clément, et and al 2014:2)
"We consider that it is important to be as independent as possible of the cognitive and student model when deciding which activities to propose." (Clément, et and al 2014:3)
"Efficient Optimization Methods" (Clément, et and al 2014:3)
"More Motivating Experience" (Clément, et and al 2014:3)
"at each time instance, the exercises that are providing the higher learning progress must be the ones proposed. This allows not only to use more efficient optimization algorithms but also to provide a more motivating experience to students." (Clément, et and al 2014:3)
"the use of highly performing Multi-Armed Bandit algorithms [5]; a simpler factored representation of the cognitive model that maps activities to the minimum necessary competence levels; and considering that the acquisition of a KC is not a binary variable but defined as the level of comprehension of that KC. The advantage of using MAB is that they are computationally efficient and require a weaker dependency between the tutoring and the cognitive and student models. Other contributions include an algorithm to estimate student competence levels; and the empirical learning progress of each activity." (Clément, et and al 2014:3)
"First, we model here the competence level of a student in a given KC as a continuous number between 0 and 1 (e.g. 0 means not acquired at all, 0:6 means acquired at 60 percent, 1 means entirely acquired). We denote ci the current estimation of this competence level for knowledge unit KCi . In what we call a R Table, for each combination of an activity a and a KCi , the expert then associates a q−value (qi (a)) which encodes the competence level required in this KCi to have maximal success in this activity a. This in turn provides a upper and lower bound on the competence level of the student: below qi (a) in case of mistake; above qi (a) in case of answering correctly." (Clément, et and al 2014:3)
"We start by assuming that each activity is represented by a set of parameters a = (a1 ; :::; ana ). The R Table then uses a factorized representation of activity parameters, where instead of considering all (a; KCi ) combinations and their corresponding qi (a), we consider only (aj ; KCi ) combinations and their corresponding qi (aj ) values, where qi (aj ) denotes the competence level in KCj required to succeed entirely in activity a which j − th parameter value is aj . This factorization makes the assumption that activity parameters are not correlated. The alternative would require a larger number of parameters and would also require more exploration in the optimization algorithm. We use the factorized R Table in the following manner to heuristically estimate the competence level qi (a) required in KCi to succeed in an activity na parameterized with a: qi (a) = qi (aj ) j =1" (Clément, et and al 2014:3)
"stealth assessment" (Clément, et and al 2014:3)
évaluation furtive (note on p.3)
"Key to the approach is the estimation of the impact of each activity over the student's competence level in each knowledge unit. This requires an estimation of the current competence level of the student for each KCi . We do not want to introduce regular tests that might interfere negatively with the learning experience of the student. Thus, competence levels need to be inferred through stealth assessment [16] that uses indirect information from the results on the exercises." (Clément, et and al 2014:3)
"When doing an activity a = (a1 ; :::; ana ), the student can either succeed or fail. In the case of success, if the estimated competence level ci in knowledge unit i is lower than qi (a), we are underestimating the competence level of the student in KCi , and so should increase it. If the student fails and qi (a) {\textless} ci , then we are overestimating the competence level of the student, and it should be decreased. For these two first cases we can define a reward: ri = qi (a) ci (1) and use it to update the estimated competence level of the student according to ci = ci + αri where α is a tunable" (Clément, et and al 2014:3)
"parameter that allows to adjust the confidence we have in each new piece of information." (Clément, et and al 2014:4)
"A crucial point is that the quantity ri = qi (a) ci is not only − used to update ci , but is used to generate an internal reward r = P ri to be cumulatively optimized for the ITS (details below). Indeed, we assume here that this is a good indicator of the learning progress over KCi resulting from doing an activity with parameters a." (Clément, et and al 2014:4)
"The intuition behind this is that if you have repeated successes in an activity for which the required competence level is higher than your current estimated competence level, this means you are probably progressing." (Clément, et and al 2014:4)
"RiARiT: Right Activity at Right Time" (Clément, et and al 2014:4)
"To address the optimization challenge for ITS, we will rely on multi-arm bandit techniques (MAB)[5]. A particularity here is that the reward (learning progress) is non-stationary, which requires specific mechanisms to track its evolution. Indeed, here a given exercise will stop providing reward, or learning progress, after the student reaches a certain competence level. Also we cannot assume that the rewards are i.i.d. as different students will have different preferences and many human factors, i.e. distraction, mistakes on using the system, create several spurious effects. Thus, we rely here on a variant of the EXP4 algorithm [1, 5]. We consider a set of filters that track how much reward each exercise parameters is giving. Then the algorithm selects stochastically the teaching activities proportionally to the expected learning progress for each parameter. Expert knowledge can also be used by incorporating coarse global constraints on the ITS. Indeed, for example the expert knows that for most students it will be useless to propose exercises about decomposition of real numbers if they do not know how to add simple integers. Thus, the expert can specify minimal competence levels in given KCi that are required to allow the ITS to try a given parameter aj of activities." (Clément, et and al 2014:4)
"ZPDES: Zone of Proximal Development and Empirical Success" (Clément, et and al 2014:4)
"Our goal is to reduce the dependency on the cognitive and student models and so we will try to simplify further the algorithm. Our simplification will take two sources of inspiration: zone of proximal development and the empirical estimation of learning progress." (Clément, et and al 2014:4)
"As discussed before focusing teaching in activities that are providing more learning progress can act as a strong motivational cue. Estimating explicitly how the success rate on each exercise is improving will remove the dependency on t Ck the R table. For this we replace Eq. 1 with r = P − k=1 t t−d Ck where Ck = 1 if the exercise at time k was solved k=1 t−d correctly. The equation compares the d + 1 more recent success with all the previous past, providing an empirical measure of how the success rate is increasing. We no longer estimate the competence level of the student, and directly use the reward estimation." (Clément, et and al 2014:4)
"improve motivation; further reduce the need of quantitative measures for the educational design expert; and provide sequence of activities that follow a more sequential order." (Clément, et and al 2014:4)
"This algorithm is identical to RiARiT but we treat the parameters that have a clear relation of increasing complexity differently. For the parameter i, when the expected learning progress of parameter j is below the level of the more complex parameter value, wi (j ) {\textless} wi (j + 1)=θ, and the success t Ck (j ) rate is higher than a pre-defined threshold : {\textgreater} k=1 t ω , we allow the parameter value j + 3 to be chosen and initiate it with: wi (j ) = 0 and wi (j + 3) = wi (j + 2)." (Clément, et and al 2014:4)
"In each exercise, one ob ject is presented with a given tagged price and the learner has to choose which combination of bank notes, coins or abstract tokens need to be taken from the wallet to buy the ob ject, with various constraints depending on exercises parameters. The five Knowledge Components aimed at in these experiments are: KnowMoney: Global skill characterizing the capability to handle money to buy ob jects in an autonomous manner; SumInteger: Capability to add and subtract integer numbers; DecomposeInteger: Capability to decompose integer numbers into groups of 10 and units; SumCents: Capability to add and subtract real numbers (cents); DecomposeCents: Capability to decompose real numbers (cents); Memory: Capability to memorize a number which is presented and then removed from visual field." (Clément, et and al 2014:4)},
file = {Clement_et_al_2014_Online_Optimization_of_Teaching_Sequences_with_Multi-Armed_Bandits.pdf:files/6732/Clement_et_al_2014_Online_Optimization_of_Teaching_Sequences_with_Multi-Armed_Bandits.pdf:application/pdf;Snapshot:files/6791/en.html:text/html},
}
@inproceedings{clement_developmental_2014,
address = {Genoa, Italy},
title = {Developmental learning for {Intelligent} {Tutoring} {Systems}},
isbn = {978-1-4799-7540-2},
url = {http://ieeexplore.ieee.org/document/6983019/},
doi = {10.1109/DEVLRN.2014.6983019},
abstract = {We present an approach to Intelligent Tutoring Systems which adaptively personalizes sequences of learning activities to maximize skills acquired by students, taking into account the limited time and motivational resources. At a given point in time, the system tries to propose to the student the activity which makes him progress best. We introduce two algorithms that rely on the empirical estimation of the learning progress, one that uses information about the difficulty of each exercise RiARiT and another that does not use any knowledge about the problem ZPDES.},
language = {en},
urldate = {2021-02-18},
booktitle = {4th {International} {Conference} on {Development} and {Learning} and on {Epigenetic} {Robotics}},
publisher = {IEEE},
author = {Clement, Benjamin and Roy, Didier and Oudeyer, Pierre-Yves and Lopes, Manuel},
month = oct,
year = {2014},
pages = {10},
file = {Clement_et_al_2014_Developmental_learning_for_Intelligent_Tutoring_Systems.pdf:files/6680/Clement_et_al_2014_Developmental_learning_for_Intelligent_Tutoring_Systems.pdf:application/pdf},
}
@article{clement_multi-armed_2015,
title = {Multi-{Armed} {Bandits} for {Intelligent} {Tutoring} {Systems}},
volume = {7},
url = {https://hal.inria.fr/hal-00913669},
abstract = {We present an approach to Intelligent Tutoring Systems which adaptively personalizes sequences of learning activities to maximize skills acquired by students, taking into account the limited time and motivational resources. At a given point in time, the system proposes to the students the activity which makes them progress faster. We introduce two algorithms that rely on the empirical estimation of the learning progress, RiARiT that uses information about the difficulty of each exercise and ZPDES that uses much less knowledge about the problem. The system is based on the combination of three approaches. First, it leverages recent models of intrinsically motivated learning by transposing them to active teaching, relying on empirical estimation of learning progress provided by specific activities to particular students. Second, it uses state-of-the-art Multi-Arm Bandit (MAB) techniques to efficiently manage the exploration/exploitation challenge of this optimization process. Third, it leverages expert knowledge to constrain and bootstrap initial exploration of the MAB, while requiring only coarse guidance information of the expert and allowing the system to deal with didactic gaps in its knowledge. The system is evaluated in a scenario where 7-8 year old schoolchildren learn how to decompose numbers while manipulating money. Systematic experiments are presented with simulated students, followed by results of a user study across a population of 400 school children.},
language = {en},
number = {2},
urldate = {2021-02-18},
journal = {Journal of Educational Data Mining},
author = {Clément, Benjamin and Roy, Didier and Oudeyer, Pierre-Yves and Lopes, Manuel},
month = jun,
year = {2015},
note = {Number: 2},
pages = {20--48},
file = {Clement_et_al_2015_Multi-Armed_Bandits_for_Intelligent_Tutoring_Systems.pdf:files/6722/Clement_et_al_2015_Multi-Armed_Bandits_for_Intelligent_Tutoring_Systems.pdf:application/pdf;Snapshot:files/6794/hal-00913669v1.html:text/html},
}
@article{gupta_interplay_2006,
title = {The {Interplay} {Between} {Exploration} and {Exploitation}},
volume = {49},
issn = {0001-4273, 1948-0989},
url = {http://journals.aom.org/doi/10.5465/amj.2006.22083026},
doi = {10.5465/amj.2006.22083026},
language = {en},
number = {4},
urldate = {2021-03-04},
journal = {Academy of Management Journal},
author = {Gupta, Anil K. and Smith, Ken G. and Shalley, Christina E.},
month = aug,
year = {2006},
note = {Number: 4},
pages = {693--706},
file = {Gupta_et_al_2006_The_Interplay_Between_Exploration_and_Exploitation.pdf:files/6731/Gupta_et_al_2006_The_Interplay_Between_Exploration_and_Exploitation.pdf:application/pdf},
}
@article{galand_motivation_2006,
title = {La motivation en situation d’apprentissage : les apports de la psychologie de l’éducation},
copyright = {© tous droits réservés},
issn = {0556-7807},
shorttitle = {La motivation en situation d’apprentissage},
url = {http://journals.openedition.org/rfp/59},
doi = {10.4000/rfp.59},
abstract = {Comment susciter ou soutenir l’intérêt des élèves pour les matières scolaires ? Comment aider les apprenants à gérer leur engagement dans les activités d’apprentissages ? Comment construire en classe un climat favorable à l’apprentissage ? Comment prévenir l’absentéisme et le décrochage scolaire ? Les questions de motivation semblent bien au cœur des défis qui se posent aujourd’hui aux acteurs de l’éducation. Nombre d’entre eux se sentent néanmoins souvent démunis face à ces questions. Les recherches sur la motivation en situation d’apprentissage ont connu des développements importants ces dernières années, notamment en psychologie de l’éducation, mais restent peu connues des professionnels. Cette situation est d’autant plus regrettable que plusieurs équipes, françaises, québécoises, suisses et belges, contribuent activement à ce courant de recherche. Ce dossier thématique donne l’opportunité à certaines de ces équipes de faire le point sur quelques questions-clés concernant la motivation, de souligner les enjeux théoriques et sociaux qui traversent leurs travaux et d’esquisser les pistes d’action qui s’en dégagent.},
language = {fr},
number = {155},
urldate = {2021-03-12},
journal = {Revue française de pédagogie. Recherches en éducation},
author = {Galand, Benoît},
month = jun,
year = {2006},
note = {ISBN: 9782734210474
Number: 155
Publisher: ENS Éditions},
pages = {5--8},
file = {Galand_2006_La motivation en situation d’apprentissage.pdf:files/6736/Galand_2006_La motivation en situation d’apprentissage.pdf:application/pdf;Snapshot:files/6682/59.html:text/html},
}
@article{gottlieb_information-seeking_2013,
title = {Information-seeking, curiosity, and attention: computational and neural mechanisms},
volume = {17},
issn = {13646613},
shorttitle = {Information-seeking, curiosity, and attention},
url = {https://linkinghub.elsevier.com/retrieve/pii/S1364661313002052},
doi = {10.1016/j.tics.2013.09.001},
language = {en},
number = {11},
urldate = {2021-03-08},
journal = {Trends in Cognitive Sciences},
author = {Gottlieb, Jacqueline and Oudeyer, Pierre-Yves and Lopes, Manuel and Baranes, Adrien},
month = nov,
year = {2013},
note = {Number: 11},
pages = {585--593},
file = {Gottlieb_et_al_2013_Information-seeking,_curiosity,_and_attention.pdf:files/6725/Gottlieb_et_al_2013_Information-seeking,_curiosity,_and_attention.pdf:application/pdf},
}
@article{romero_numerique_2020,
title = {Le numérique va révolutionner l'éducation … vraiment ?},
url = {https://hal.inria.fr/hal-02895694},
abstract = {Nous entendons ou lisons très souvent-notamment dans binaire-que le numérique bouleverse à peu près toutes les facettes de nos vies. Que ce soit la médecine, le transport, l'industrie, le divertissement, quasiment tous les secteurs d'activité connaissent de profondes évolutions dues à l'informatique et ses applications. A première vue, l'éducation ne semble pas échapper à la règle si l'on croit les analyses les plus répandues. Gérard Giraudon et Margarida Romero, deux experts du numérique pour l'éducation, décryptent pour nous une vidéo de Derek Muller expliquant pourquoi ce n'est pas si simple. Pascal Guitton \& Thierry Viéville. Depuis le début du 20ième siècle, nos sociétés ont connu nombre de révolutions technologiques (thermodynamique, nucléaire, informatique...) qui ont impacté la plupart des domaines (industrie, transports, commerce, agriculture, média...). Mises à part quelques exceptions, l'éducation n'en fait pas partie et les cours sont toujours donnés par un·e seul·e enseignant·e à des groupes d'élèves réunis dans une salle de classe. Certains pourraient reprocher cet état … à l'inertie de l'institution. Mais l'une des raisons pour laquelle la technologie n'a pas révolutionné l'éducation est au coeur même de ce qui est son rôle spécifique : créer un contexte social et relationnel adapté pour accompagner dans l'apprentissage des savoirs scolaires et des compétences nécessaires. Les apprentissages scolaires ne se produisent pas spontanément par la simple socialisation de l'enfant (Tricot, 2014) : il est nécessaire d'organiser les situations d'apprentissage. A l'école, ces savoirs se développent dans un contexte scolaire et social avec d'autres apprenant·e·s et des enseignant·e·s attentionné·e·s. Dans une vidéo publiée en 2014, Derek Muller de Veritasium démystifie ces "révolutions" technologiques et place l'enseignant·e au coeur d'une relation éducative essentielle pour engager les élèves dans les activités d'apprentissage. Au delà de l'engagement et l'autonomisation de l'apprenant·e soulignés par Muller, nous devons également considérer le rôle des enseignant·e·s au niveau de l'ingénierie des activités d'apprentissage et de leur orchestration, sans oublier les précieuses rétroactions qui contribuent, plus généralement, aux apprentissages. https://youtu.be/GEmuEWjHr5c Au delà de la vidéo Oui « le rôle fondamental d'un enseignant n'est pas de fournir des informations, mais de guider le processus social d'apprentissage ; le travail d'un enseignant est d'inspirer, de mettre au défi, de motiver ses élèves à vouloir apprendre ». Et l'enseignant n'est pas qu'un animateur charismatique, il doit aussi avoir un rôle d'ingénieur pédagogique et de régulateur externe des processus d'apprentissage pendant l'activité et apporter des rétroactions permettant l'évaluation formative. Comme l'explique très bien André Tricot en partageant les études sur les innovations pédagogiques et apprendre avec le numérique (voir par exemple cette présentation vidéo), le numérique est souvent un outil de plus, qui n'apporte pas en soi, d'innovation pédagogique. L'innovation technologique apportée par des technologies comme la réalité augmentée (RA), réalité virtuelle (RV) ou encore la robotique pédagogique et les approches de fabrication numérique (maker) changent la médiation des échanges.},
language = {fr},
urldate = {2021-03-12},
journal = {Binaire},
author = {Romero, Margarida and Giraudon, Gérard},
month = jul,
year = {2020},
file = {Romero_Giraudon_2020_Le numérique va révolutionner l'éducation … vraiment.pdf:files/6727/Romero_Giraudon_2020_Le numérique va révolutionner l'éducation … vraiment.pdf:application/pdf;Snapshot:files/6684/hal-02895694.html:text/html},
}
@article{romero_jeu_2019,
title = {Le jeu du robot : analyse d’une activité d’informatique débranchée sous la perspective de la cognition incarnée.},
volume = {13},
shorttitle = {Le jeu du robot},
url = {https://hal.inria.fr/hal-02144467},
doi = {10.26220/rev.3089},
abstract = {Les activités d’informatique débranchée se sont popularisées en même temps que l’introduction de l’apprentissage de l’informatique à l’école. Dans cet article nous analysons le potentiel pédagogique d’activités d’informatique débranchée sous la perspective des sciences de l'éducation. Les théories en lien avec la cognition incarnée nous servent de cadre d’analyse d’activités d’informatique débranchée comme le jeu du robot, où l’une ou l’un des participant·e·s joue par exemple le rôle d’une programmeuse et l’autre d’un objet programmable comme un robot. Ce jeu du robot nous permettra de discuter le potentiel des activités d’informatique débranchée en lien avec les repères dans l’espace, y compris le besoin de transposition du plan à l’espace, en tenant compte du potentiel de la cognition incarnée.},
language = {fr},
number = {1},
urldate = {2021-04-07},
journal = {Review of science, mathematics and ICT education},
author = {Romero, Margarida and Duflot, Marie and Viéville, Thierry},
month = jun,
year = {2019},
note = {Number: 1},
file = {Romero_et_al_2019_Le_jeu_du_robot.pdf:files/6726/Romero_et_al_2019_Le_jeu_du_robot.pdf:application/pdf},
}
@book{menon_going_2019,
title = {Going beyond digital literacy to develop computational thinking in {K}-12 education,},
isbn = {978-0-367-33379-9},
url = {https://hal.inria.fr/hal-02281037},
abstract = {In the past decade, digital learning has contributed to the transformation of K-12 education by using a variety of technology-enhanced pedagogical approaches, and it helps understand the basics of computational thinking (CT). In the area of CT for young learners, educators are experimenting with digital or digital-inspired methods to go beyond digital literacy, towards also improving other skills, such as problem-solving, logical thinking and abstraction. By improving these skills, we aim to empower learners with the required knowledge as technology users and to aid in mastering the technology to develop their creative and citizenship potential through them. This chapter will provide a literature review on studies conducted to teach computer programming and computational concepts to K-12 students using visual programming tools, unplugged activities and educational robotics while evaluating how it can also help improve CT skills.},
language = {en},
urldate = {2021-04-07},
publisher = {Taylor\&Francis (Routledge)},
author = {Menon, Divya and Bp, Sowmya and Romero, Margarida and Viéville, Thierry},
year = {2019},
file = {Menon_et_al_2019_Going_beyond_digital_literacy_to_develop_computational_thinking_in_K-12.pdf:files/6735/Menon_et_al_2019_Going_beyond_digital_literacy_to_develop_computational_thinking_in_K-12.pdf:application/pdf;Snapshot:files/6685/hal-02281037v1.html:text/html},
}
@techreport{barnabe_low-cost_2020,
type = {report},
title = {A low-cost tabletop game to collect learning analytics during computational thinking using unplugged or tangible activities},
url = {https://hal.inria.fr/hal-03040909},
abstract = {We report on a new setup allowing us to collect learning analytics (LA) during computational thinking unplugged or tangible playful activities. We target the development of computational thinking (CT) competency, including the initiation to informatics (i.e., computer science and technology), with the goal to evaluate and analyze the development of CT. Collecting LA is mandatory in this case and if adaptive learning is targeted. While collecting LA during online interactions is rather straightforward, automatically collecting LA when manipulating tangible objects is more challenging, especially in a context where low-cost greenIT material is required. The key idea here, contrary to usual “black-box” systems working (more or less) automatically, is to change the learning paradigm and involve the learner in the data collection, making the process transparent and allowing her or him to also learn how to learn. This is particularly pertinent here since we use Informatics tools in order to … initiate to Informatics and CT. This means that we have to redesign the activity scenario including its didactic and revisit the underneath pedagogy, which turns to be an interesting and innovative challenge.},
language = {en},
urldate = {2021-04-08},
institution = {Inria},
author = {Barnabé, Sabrina and Denet, Lola and Manrique, Mathieu and Menon, Divya and Pascual, Eric and Romero, Margarida and Viéville, Thierry},
month = dec,
year = {2020},
file = {Barnabe_et_al_2020_A_low-cost_tabletop_game_to_collect_learning_analytics_during_computational.pdf:files/6737/Barnabe_et_al_2020_A_low-cost_tabletop_game_to_collect_learning_analytics_during_computational.pdf:application/pdf},
}
@article{alexandre_modeles_2000,
title = {Modèles connexionnistes de la mémoire},
url = {https://hal.inria.fr/inria-00099242},
abstract = {Malgré des liens originellement très forts avec les neurosciences, l'informatique aujourd'hui reste avant tout une science essentiellement orientée vers des citères d'efficacité et de fiabilité. Par exemple, la mémoire d'un ordinateur a très peu de rapports avec la mémoire d'un être vivant. Toutefois, plusieurs domaines de l'informatique se préoccupent de ce type de modélisation. En particulier, le connexionnisme, qui élabore des réseaux de neurones artificiels, utilise un formalisme de calcul inspiré de celui du cerveau. Nous présentons ici différents types de mémoire réalisables par des réseaux de neurones artificiels, qu'ils soient d'inspiration statistique ou biologique, et nous discutons de leurs rapports avec la mémoire humaine et de leur intérêt potentiel pour le biologiste ou le thérapeute.},
language = {fr},
number = {55},
urldate = {2021-04-14},
journal = {Thérapie},
author = {Alexandre, Frédéric},
year = {2000},
note = {Number: 55},
pages = {525},
file = {Snapshot:files/6689/inria-00099242.html:text/html},
}
@techreport{markowski_types_nodate,
title = {Types et rôle de la mémoire humaine},
language = {fr},
author = {Markowski, Grzegorz},
pages = {6},
file = {Markowski_Types_et_role_de_la_memoire_humaine.pdf:files/6688/Markowski_Types_et_role_de_la_memoire_humaine.pdf:application/pdf},
}
@book{besnier_les_2021,
edition = {Presses Universitaires de France},
series = {Que sais-je ?},
title = {Les théories de la connaissance},
isbn = {978-2-7154-0603-2},
url = {http://www.cairn.info/les-theories-de-la-connaissance--9782715406032.htm},
abstract = {Élaborer une théorie de la connaissance, c’est s’attacher à démonter les mécanismes producteurs du savoir, identifier les présupposés théoriques et les implications métaphysiques qui en règlent l’exercice. C’est aussi interroger les dimensions métaphysiques et éthiques que révèle tout acte de connaître. Jean-Michel Besnier nous présente et nous explique les modèles épistémologiques qui rendent compte de l’acquisition des connaissances. Il situe l’apport contemporain des sciences cognitives dans le sillage des conceptions philosophiques traditionnelles.},
language = {fr},
urldate = {2021-05-25},
author = {Besnier, Jean-Michel},
month = may,
year = {2021},
note = {ISSN: 0768-0066},
file = {Snapshot:files/6693/les-theories-de-la-connaissance--9782715406032.html:text/html},
}
@article{frayssinhes_competence_2019,
series = {Quelle reconnaissance des compétences transversales ?},
title = {Compétence, expérience, connaissances et savoirs transférables},
url = {https://hal.archives-ouvertes.fr/hal-02939062},
number = {218},
urldate = {2021-05-21},
journal = {Éducation permanente},
author = {Frayssinhes, Jean},
month = apr,
year = {2019},
note = {Number: 218
Publisher: Arcueil : Éducation permanente},
keywords = {Compétence, Connaissances, Expérience, Transferable knowledge},
pages = {43--54},
file = {Frayssinhes_2019_Compétence, expérience, connaissances et savoirs transférables.pdf:files/6742/Frayssinhes_2019_Compétence, expérience, connaissances et savoirs transférables.pdf:application/pdf},
}
@article{biard_theorie_2019,
title = {La théorie de la connaissance entre sémiologie et ontologie},
url = {https://halshs.archives-ouvertes.fr/halshs-02156623},
abstract = {Dans la 3e question sur le livre I des Sentences, Pierre d’Ailly est conduit à se demander « qu’est-ce que la connaissance ou cognition (quid sit notitia sive cognitio) ? » Après l’avoir présentée comme une sorte d’acte, Pierre d’Ailly cherche à déterminer la relation à une faculté cognitive qui seule peut en faire formellement une notitia. On retrouve dans ce passage un certain nombre d’expressions et de propositions qui sont également présentes dans le Conceptus. Dans ces deux textes de Pierre d’Ailly s’articulent certaines thèses sur le statut ontologique de la connaissance (acte, disposition, accident) et d’autres sur la fonction sémiologique ou représentationnelle du concept, chacune de ces approches apparaissant également indispensable pour définir la connaissance. Par là Pierre d’Ailly occupe une place importante dans l’histoire de des théories du langage et de la connaissance. Après avoir poussé au plus loin, dans le Conceptus, la résorption du langage parlé dans le langage mental, il réintroduit l’idée d’un usage instrumental des mots dans d’autres textes, mais il ne néglige pas pour autant la question du statut métaphysique de cet élément de base qu’est le concept comme connaissance, notitia.},
language = {fr},
urldate = {2021-05-25},
author = {Biard, Joël},
month = jun,
year = {2019},
note = {Publisher: Académie des Inscriptions et Belles Lettres ; De Boccard},
pages = {85},
file = {Snapshot:files/6692/halshs-02156623.html:text/html},
}
@article{collins_apprentissage_nodate,
title = {Apprentissage et contrôle cognitif: une théorie computationnelle de la fonction exécutive préfontale humaine},
language = {fr},
author = {Collins, Anne},
pages = {252},
file = {Collins_Apprentissage_et_controle_cognitif.pdf:files/6749/Collins_Apprentissage_et_controle_cognitif.pdf:application/pdf},
}
@article{goldman_croyance_2005,
title = {La croyance : aux confins mystérieux de la cognition},
volume = {25},
issn = {2-8041-4717-7},
shorttitle = {La croyance},
url = {https://www.cairn.info/revue-cahiers-de-psychologie-clinique-2005-2-page-87.htm},
doi = {10.3917/cpc.025.0087},
abstract = {Les neurosciences cognitives permettent de définir l'activité mentale sur base de fonctions dont les substrats cérébraux sont aujourd'hui mieux connus, principalement grâce à la neuroimagerie fonctionnelle. La reconnaissance de ces substrats cérébraux ouvre de nouvelles perspectives sur des processus tels que la croyance. Toutes les fonctions cognitives, qu'elles touchent principalement à l'individu ou à la relation de celui-ci avec son entourage, fournissent un champ d'application à la croyance. Dans ses formes les plus élaborées, la croyance interagit avec des activités cognitives complexes, touchant à la perception du corps, de l'espace et du temps, à la mémoire, au sens moral et à la représentation de la pensée d'autrui (“Theory of Mind”). Des constantes apparaissent dans la relation qu'entretient la croyance avec chacune des fonctions cognitives que les neurosciences ont mises à jour. Dans une perspective neurocognitive, la croyance pourrait assurer une fonction, celle de soulager l'activité mentale de la résolution de conflits internes. Suivant une hypothèse avancée, l'émergence de cette fonction aurait principalement répondu aux conflits qui naissent de l'état d'incertitude attaché à la conscience humaine. La croyance impliquerait donc un réseau de structures neuronales qui gèrent les choix d'une pensée vouée au doute et à l'espérance.},
language = {FR},
number = {2},
journal = {Cahiers de psychologie clinique},
author = {Goldman, Serge},
year = {2005},
note = {Number: 2
Place: Louvain-la-Neuve
Publisher: De Boeck Supérieur},
pages = {87--109},
file = {Goldman_2005_La croyance.pdf:files/6739/Goldman_2005_La croyance.pdf:application/pdf;Snapshot:files/6691/revue-cahiers-de-psychologie-clinique-2005-2-page-87.html:text/html},
}
@book{bourassa_neurosciences_2017,
address = {Louvain-la-Neuve},
series = {Pédagogies en développement},
title = {Neurosciences et éducation. {Pour} apprendre et accompagner},
isbn = {978-2-8073-0748-3},
url = {https://www.cairn.info/neurosciences-et-education--9782807307483.htm},
abstract = {Destiné aux étudiants en formation initiale à l’enseignement et aux enseignants, l'ouvrage explique de quelle manière les neurosciences peuvent éclairer l’apprentissage et soutenir l’élaboration de stratégies pédagogiques et orthopédagogiques adaptées.
Dans cet ouvrage, les trois auteures, formatrices d’enseignants, conjuguent leur expertise pour examiner de quelle manière les neurosciences peuvent éclairer l’apprentissage et soutenir l’élaboration de stratégies pédagogiques et orthopédagogiques adaptées. Elles proposent des réponses ou, mieux dit, des hypothèses de travail aux questions que se posent formateurs et enseignants dans l’exercice de leur métier.
À cette fin, ce livre, dont le lecteur est le héros, offre à tout moment la latitude de choisir où se rendre. Si le lecteur souhaite examiner sa pratique en posture « méta », il sera intéressé par le profil apprenant présenté dans la première partie. S’il se demande ce qu’il doit comprendre quand l’autre ne comprend pas, la deuxième partie lui offrira de nombreuses pistes. S’il cherche quelle approche privilégier en individuel ou en collectif, il lira les coins de l’intervention. S’il veut savoir comment les neurosciences aident à comprendre pourquoi certaines stratégies marchent mieux que d’autres, il lira les coins de la réflexion. Enfin, s’il se demande comment raconter le fonctionnement du cerveau à ses élèves, il choisira les coins de l’expérimentation.
Ce livre s’adresse à tout enseignant qui souhaite retrouver le plaisir d’exercer ce métier impossible, comme Freud se plaisait à le qualifier. Il s’adresse aussi à tout formateur d’enseignants qui souhaite instaurer une culture enseignante fondée sur le plaisir d’apprendre à apprendre toute la vie.},
language = {FR},
publisher = {De Boeck Supérieur},
author = {Bourassa, Michelle and Menot-Martin, Mylène and Philion, Ruth},
year = {2017},
}
@article{chang_les_2015,
title = {Les apprentissages à l’heure des technologies cognitives numériques},
volume = {146},
url = {https://www.cairn.info/revue-administration-et-education-2015-2-page-91.htm},
doi = {10.3917/admed.146.0091},
language = {FR},
number = {2},
journal = {Administration \& Éducation},
author = {Chang, Chun-Yen and Tijus, Charles and Zibetti, Elisabetta},
year = {2015},
note = {Number: 2
Place: Paris
Publisher: Association Française des Acteurs de l'Éducation},
pages = {91--98},
}
@book{math_neurosciences_2008,
address = {Louvain-la-Neuve},
series = {Neurosciences \& cognition},
title = {Neurosciences cliniques. {De} la perception aux troubles du comportement},
isbn = {978-2-8041-5672-5},
url = {https://www.cairn.info/neurosciences-cliniques--9782804156725.htm},
abstract = {Cet ouvrage unique en langue française aborde les divers aspects des neurosciences comportementales sous l'angle clinique.
Il présente les notions essentielles de psychologie et psychiatrie biologiques, de même qu’en neurologie clinique, en mettant l’accent sur les organes sensoriels, leur rôle dans l'initiation des comportements humains et leurs défaillances dans diverses altérations neurologiques ou neuropsychiatriques.},
language = {FR},
publisher = {De Boeck Supérieur},
author = {Math, François},
year = {2008},
}
@book{lieury_introduction_2020,
address = {Paris},
series = {Psycho {Sup}},
title = {Introduction à la psychologie cognitive},
volume = {2e ed.},
isbn = {978-2-10-080186-2},
url = {https://www.cairn.info/introduction-a-la-psychologie-cognitive--9782100801862.htm},
abstract = {Véritable outil d'initiation, cet ouvrage, à jour des dernières recherches menées en psychologie cognitive, décrit précisément et de façon pédagogique les différents champs de cette discipline.Sont ainsi successivement abordés l’histoire et les grands secteurs de la psychologie cognitive, et les grands thèmes classiques de ce domaine, en s’appuyant sur des exemples issus de grandes découvertes et théories, comme la vision des couleurs, l’intelligence ou la personnalité.},
language = {FR},
publisher = {Dunod},
author = {Lieury, Alain and Léger, Laure},
year = {2020},
}
@book{houde_raisonnement_2018,
address = {Paris cedex 14},
series = {Que sais-je ?},
title = {Le raisonnement},
volume = {2e éd.},
isbn = {978-2-13-080389-8},
url = {https://www.cairn.info/le-raisonnement--9782130803898.htm},
abstract = {Comment apprend-on à réfléchir ? Depuis quelques années, les neurosciences cognitives et la psychologie se sont penchées sur notre cerveau pour l’observer quand il raisonne. Ou plutôt quand il se trompe, s’arrête, corrige ses erreurs, reconfigure ses circuits de neurones, cherche du neuf en inhibant l’ancien ou le trop habituel. Les récentes découvertes scientifiques ont, en effet, mis en lumière que le plus souvent nous pensons trop vite, cédant à nos intuitions et à des réponses impulsives plutôt que de prendre le temps de correctement réfléchir.
Olivier Houdé nous invite à comprendre comment l’être humain raisonne dès le plus jeune âge et quel rôle jouent la pédagogie et les émotions dans ce processus. À l’aide d’exercices concrets que chacun peut réaliser, il nous fait découvrir les principes essentiels de notre façon si humaine de raisonner, d’apprendre, d’inventer.},
language = {FR},
publisher = {Presses Universitaires de France},
author = {Houdé, Olivier},
year = {2018},
}
@book{houde_psychologie_2020,
address = {Paris cedex 14},
series = {Que sais-je ?},
title = {La {Psychologie} de l'enfant},
volume = {9e éd.},
isbn = {978-2-7154-0489-2},
url = {https://www.cairn.info/la-psychologie-de-l-enfant--9782715404892.htm},
abstract = {De nouvelles découvertes sur le développement du cerveau et de l’intelligence ont modifié en profondeur nos connaissances sur la psychologie de l’enfant. À partir d’expériences simples que chacun peut réaliser à la maison ou à l’école, mais aussi en faisant le point sur les apports des sciences cognitives à propos du bébé, de l’enfant et de l’adulte, cet ouvrage explique avec clarté comment se construit la cognition humaine.Tout en rendant hommage à l’œuvre de Jean Piaget, le plus grand psychologue de l’enfant au XXe siècle, Olivier Houdé réexamine sa théorie et propose ici une conception nouvelle du développement de l’intelligence.À lire également en Que sais-je ?...Les 100 mots de la psychologie, Olivier HoudéLes 100 mots de l’enfant, sous la direction de Jacques André},
language = {FR},
publisher = {Presses Universitaires de France},
author = {Houdé, Olivier},
year = {2020},
}
@incollection{george_labduction_1997,
address = {Paris cedex 14},
series = {Psychologie et sciences de la pensée},
title = {L’abduction et l’explication},
isbn = {978-2-13-048046-4},
url = {https://www.cairn.info/polymorphisme-du-raisonnement-humain--9782130480464-p-113.htm},
abstract = {Cette édition numérique a été réalisée à partir d’un support physique, parfois ancien, conservé au sein du dépôt légal de la Bibliothèque nationale de France, conformément à la loi n° 2012-287 du 1er mars 2012 relative à l’exploitation des Livres indisponibles du XXe siècle.},
language = {FR},
booktitle = {Polymorphisme du raisonnement humain},
publisher = {Presses Universitaires de France},
author = {George, Christian},
year = {1997},
pages = {113--128},
}
@book{masmoudi_du_2010,
address = {Louvain-la-Neuve},
series = {Neurosciences \& cognition},
title = {Du percept à la décision. {Intégration} de la cognition, l’émotion et la motivation},
isbn = {978-2-8041-3798-4},
url = {https://www.cairn.info/du-percept-a-la-decision--9782804137984.htm},
abstract = {L'objectif de cet ouvrage est de réunir des chercheurs, venant d'horizons théoriques et disciplinaires différents, autour d'une approche intégrative de la cognition, de l'émotion et de la motivation.},
language = {FR},
publisher = {De Boeck Supérieur},
author = {Masmoudi, Slim and Naceur, Abdelmajid},
year = {2010},
}
@book{collective_motivation_2017,
address = {Auxerre},
series = {Petite bibliothèque},
title = {La motivation},
isbn = {978-2-36106-427-3},
url = {https://www.cairn.info/la-motivation--9782361064273.htm},
abstract = {Pourquoi l’élève s’investit-il à l’école ? Qu’est-ce qui fait courir le sportif ? Pourquoi s’engage-t-on dans un travail fastidieux ? Quelles motivations guident nos choix, nos achats, notre vote ?
La recherche en sciences humaines a multiplié les théories et expériences depuis un demi-siècle, dans le sillon du behaviorisme. Elle ne fournit pas de recettes, et d’une certaine manière, heureusement. Mais elle parvient de mieux en mieux à identifier les ingrédients nécessaires : le sentiment d’efficacité personnelle, la façon dont on aborde ses propres contre-performances, l’interaction avec une personne de confiance, la capacité d’autodétermination, le besoin de reconnaissance…
Recourant aussi bien à la psychologie qu’aux sciences de l’éducation ou à l’addictologie, ce livre dresse un état des lieux des savoirs actuels et dégage des pistes concrètes pour motiver les autres, et mieux se motiver soi-même. Après avoir présenté les grandes théories de la motivation, il s’intéresse aux relations entre motivation et apprentissages, explore le thème de la motivation au travail et pose in fine la question des troubles de la motivation.},
language = {FR},
publisher = {Éditions Sciences Humaines},
author = {Collective},
year = {2017},
}
@incollection{delacour_conscience_2001,
address = {Louvain-la-Neuve},
series = {Neurosciences \& cognition},
title = {Conscience et cerveau - {Introduction}},
isbn = {978-2-8041-3766-3},
url = {https://www.cairn.info/conscience-et-cerveau--9782804137663-p-5.htm},
language = {FR},
booktitle = {Conscience et cerveau},
publisher = {De Boeck Supérieur},
author = {Delacour, Jean},
year = {2001},
pages = {5--8},
}
@incollection{bouchon-meunier_raisonnement_2007,
address = {Paris cedex 14},
series = {Que sais-je ?},
title = {Raisonnement possibiliste},
volume = {4e éd.},
isbn = {978-2-13-056260-3},
url = {https://www.cairn.info/la-logique-floue--9782130562603-p-97.htm},
abstract = {La logique floue permet de résoudre tous les problèmes dans lesquels on dispose de connaissances imprécises, soumises à des incertitudes de nature non probabiliste. Elle peut être appliquée dans presque tous les domaines. Cet ouvrage se propose d'expliquer en quoi consiste cette technique et ce qu'elle peut apporter à ses utilisateurs. Il présente les éléments méthodologiques indispensables aux applications allant du plus simple au plus complexe.},
language = {FR},
booktitle = {Que sais-je? {La} logique {Floue}},
publisher = {Presses Universitaires de France},
author = {Bouchon-Meunier, Bernadette},
year = {2007},
pages = {97--103},
file = {Bouchon-Meunier_2007_Raisonnement_possibiliste.pdf:files/7029/Bouchon-Meunier_2007_Raisonnement_possibiliste.pdf:application/pdf},
}
@book{bouchon-meunier_logique_2007,
address = {Paris cedex 14},
series = {Que sais-je ?},
title = {La logique floue},
volume = {4e éd.},
isbn = {978-2-13-056260-3},
url = {https://www.cairn.info/la-logique-floue--9782130562603.htm},
abstract = {La logique floue permet de résoudre tous les problèmes dans lesquels on dispose de connaissances imprécises, soumises à des incertitudes de nature non probabiliste. Elle peut être appliquée dans presque tous les domaines. Cet ouvrage se propose d'expliquer en quoi consiste cette technique et ce qu'elle peut apporter à ses utilisateurs. Il présente les éléments méthodologiques indispensables aux applications allant du plus simple au plus complexe.},
language = {FR},
publisher = {Presses Universitaires de France},
author = {Bouchon-Meunier, Bernadette},
year = {2007},
note = {Issue: 2702},
}
@article{pailler_spinoza_2004,
title = {Spinoza avait raison.{Joie} et tristesse, le cerveau des émotions, d'{Antonio} {R}. {Damasio}},
volume = {25},
issn = {2130544401},
shorttitle = {Spinoza avait raison.},
url = {https://www.cairn.info/revue-francaise-de-psychosomatique-2004-1-page-165.htm},
doi = {10.3917/rfps.025.0165},
language = {FR},
number = {1},
journal = {Revue française de psychosomatique},
author = {Pailler, Jean-Jacques},
year = {2004},
note = {Number: 1
Place: Paris cedex 14
Publisher: Presses Universitaires de France},
pages = {165--172},
}
@book{carre_traite_2019,
address = {Paris},
series = {Éducation {Sup}},
title = {Traité de psychologie de la motivation. {Théories} et pratiques},
isbn = {978-2-10-078304-5},
url = {https://www.cairn.info/traite-de-psychologie-de-la-motivation--9782100783045.htm},
abstract = {Cet ouvrage synthétise l'ensemble des savoirs théoriques et pratiques sur la motivation. Véritable état des savoirs sur ce champ de recherche, il fait le point sur les perspectives théoriques et les implications pratiques de ce concept majeur de la psychologie.},
language = {FR},
publisher = {Dunod},
author = {Carré, Philippe and Fenouillet, Fabien},
year = {2019},
}
@article{tcherkassof_les_2014,
title = {Les émotions : une conception relationnelle},
volume = {114},
url = {https://www.cairn.info/revue-l-annee-psychologique1-2014-3-page-501.htm},
doi = {10.4074/S0003503314003042},
abstract = {Résumé
Dans la vie courante, le terme émotion désigne en premier lieu des phénomènes expérientiels qui sortent de l’ordinaire. En raison des mouvements de l’âme qui les caractérisent, Descartes a désigné ces phénomènes par le terme émotion, un mot qui à son époque signifiait émeute ou agitation. Aristote reconnaissait le même phénomène dans son emploi du mot kinèsis. En effet, les ressentis émotionnels sont des perceptions de l’engagement dynamique du corps dans l’interaction. Pourtant, la qualité cinesthésique des émotions a été délaissée par la plupart des théories psychologiques. Cet article présente les arguments plaidant en faveur d’un modèle perceptif de l’émotion qui défend l’idée que les émotions sont des attitudes corporelles exprimant la relation du sujet à l’objet émotionnel. Ces arguments sont basés sur les récentes avancées des sciences cognitives notamment en matière de cognition incarnée. Ce modèle perceptif décrit une séquence fonctionnelle du processus de l’émotion qui s’inscrit dans la perspective des théories multi-componentielles actuelles des émotions.},
language = {FR},
number = {3},
journal = {L’Année psychologique},
author = {Tcherkassof, Anna and Frijda, Nico H.},
year = {2014},
note = {Number: 3
Place: Paris
Publisher: NecPlus},
pages = {501--535},
}
@article{roy_approche_2015,
title = {Approche neuropsychologique des fonctions exécutives de l’enfant : état des lieux et éléments de prospective},
volume = {7},
url = {https://www.cairn.info/revue-de-neuropsychologie-2015-4-page-245.htm},
doi = {10.3917/rne.074.0245},
abstract = {RésuméEn l’espace de 30 ans, les travaux consacrés au développement typique et perturbé des fonctions exécutives (FE) de l’enfant ont connu un essor considérable. Ce phénomène s’explique en particulier par les perspectives scientifiques majeures associées à l’étude de ces processus de contrôle de haut niveau et leur rôle déterminant pour approcher le développement psychologique de l’enfant au sens large. Les recherches dans ce domaine ont progressivement conduit à la formalisation de modèles théoriques intégratifs et la mise en perspective de liens fonctionnels étroits avec d’autres concepts essentiels de la psychologie. L’exploration des perturbations des FE et leur description sémiologique dans divers contextes cliniques pédiatriques a également progressé, tandis que les outils d’évaluation se sont à la fois généralisés et diversifiés. Malgré ces progrès considérables, plusieurs insuffisances sont à signaler, que ce soit en termes de modélisation théorique du développement typique, d’expertise clinique ou d’évaluation. Des pistes de recherche complémentaires sont proposées, afin de fournir des repères prospectifs qui soient de nature à améliorer les connaissances relatives à la neuropsychologie des FE de l’enfant dans les prochaines années.},
language = {FR},
number = {4},
journal = {Revue de neuropsychologie},
author = {Roy, Arnaud},
year = {2015},
note = {Number: 4
Place: Montrouge
Publisher: John Libbey Eurotext},
pages = {245--256},
}
@incollection{censabella_chapitre_2007,
address = {Wavre},
series = {{PSY}-Évaluation, mesure, diagnostic},
title = {Chapitre 5 : les fonctions exécutives},
isbn = {978-2-87009-964-3},
url = {https://www.cairn.info/bilan-neuropsychologique-de-l-enfant--9782870099643-p-117.htm},
abstract = {La neuropsychologie a connu un essor considérable. Chez l’enfant, cette approche théorique a montré tout son sens dans l’étude des troubles cognitifs liés à des atteintes cérébrales acquises, certaines pathologies génétiques ou métaboliques, ou encore des troubles développementaux, y compris les troubles d’apprentissage.
Cet ouvrage est un guide pour la pratique clinique de ceux qui souhaitent utiliser l’approche neuropsychologique dans l’analyse des difficultés cognitives des enfants. Le bilan neuropsychologique permet, en effet, de dessiner le profil cognitif de l’enfant, de détailler ses forces et ses faiblesses en vue de concevoir une prise en charge la plus adaptée possible à ses difficultés spécifiques. Chaque chapitre traite d’un domaine cognitif particulier, comme la mémoire, l’attention, les fonctions exécutives, l’analyse visuo-spatiale, le langage oral ou écrit, etc.},
language = {FR},
booktitle = {Bilan neuropsychologique de l'enfant},
publisher = {Mardaga},
author = {Censabella, Sandrine},
year = {2007},
pages = {117--137},
file = {Censabella_2007_Chapitre_5.pdf:files/7112/Censabella_2007_Chapitre_5.pdf:application/pdf;Chapitre 5 \: les fonctions exécutives | Cairn.info:files/6776/bilan-neuropsychologique-de-l-enfant--9782870099643-page-117.html:text/html},
}
@article{goutte_traitement_2011,
title = {Traitement des émotions dans les pathologies neurodégénératives : une revue de la littérature},
volume = {3},
url = {https://www.cairn.info/revue-de-neuropsychologie-2011-3-page-161.htm},
doi = {10.3917/rne.033.0161},
abstract = {RésuméLes pathologies dégénératives sont accompagnées non seulement de déficits cognitifs, mais également de troubles émotionnels, troubles qui ont une incidence sur la vie sociale et familiale des patients et de leur entourage. Un certain nombre d’études ont mis en évidence des déficits importants de reconnaissance, d’identification, de discrimination ou d’appariement de certaines émotions dans différents syndromes démentiels. Cependant, ces atteintes ne sont pas homogènes entre toutes les démences ; elles peuvent, selon le cas, affecter une ou plusieurs émotions. Le degré de l’altération émotionnelle peut également varier d’une pathologie à l’autre. Ces déficits dans le traitement des émotions sont mis en relation avec les atrophies des régions cérébrales observées dans le vieillissement pathologique et qui concernent principalement l’amygdale, le cortex orbitofrontal et les ganglions de la base. Dans cet article, nous proposons une revue de la littérature des études comportementales menées sur le traitement des émotions dans la maladie d’Alzheimer, la dégénérescence lobaire fronto-temporale, la maladie de Parkinson, la maladie de Huntington et la paralysie supranucléaire progressive. Nous présentons également les principaux modèles cognitifs et discutons des régions cérébrales impliquées dans le traitement des émotions.},
language = {FR},
number = {3},
journal = {Revue de neuropsychologie},
author = {Goutte, Virginie and Ergis, Anne-Marie},
year = {2011},
note = {Number: 3
Place: Montrouge
Publisher: John Libbey Eurotext},
pages = {161--175},
}
@book{boutinet_abc_2009,
address = {Toulouse},
series = {Éducation - {Formation}},
title = {L'{ABC} de la {VAE}},
isbn = {978-2-7492-1109-1},
url = {https://www.cairn.info/l-abc-de-la-vae--9782749211091.htm},
abstract = {Depuis que la loi de Modernisation sociale du 17 janvier 2002 reconnaît à toute personne le droit de faire valider les acquis de son expérience en vue de l'obtention, en totalité ou en partie, d'un diplôme, d'un titre à finalité professionnelle ou d'un certificat de qualification professionnelle, cette deuxième voie d'accès à une certification à côté des cursus traditionnels de formation s'est plus ou moins amplifiée suivant les secteurs d'activités ; mais elle a suscité ici et là tantôt enthousiasme, tantôt résistance ou pour le moins une très grande méfiance.
Le présent lexique veut explorer le champ sémantique, encore très mouvant de cette nouvelle pratique de formation professionnelle. Il permet d'en identifier les premiers repères et d'en favoriser l'accès. A travers la définition de 80 concepts, il représente une contribution originale, homogène, stimulante et relativement exhaustive de la VAE et de ses enjeux.
Il a été réalisé par un réseau large de praticiens et chercheurs connus au niveau français pour leurs préoccupations ou leurs expertises professionnelles ou scientifiques autour de la VAE.},
language = {FR},
publisher = {Érès},
author = {Boutinet, Jean-Pierre},
year = {2009},
}
@inproceedings{aubret_etude_2019,
address = {Toulouse, France},
title = {Étude de la motivation intrinsèque en apprentissage par renforcement},
url = {https://hal.archives-ouvertes.fr/hal-02272091},
urldate = {2021-07-29},
booktitle = {Journées {Francophones} sur la {Planification}, la {Décision} et l'{Apprentissage} pour la conduite de systèmes},
author = {Aubret, Arthur and Matignon, Laëtitia and Hassas, Salima},
month = jul,
year = {2019},
keywords = {intrinsic motivation, Reinforcement learning, curiosité, curiosity, empowerment, génération d'objectifs, generation of objectives, knowledge acquisition, meta-reward, motivation intrinsèque, options, Knowledge Acquisition, Reinforcement Learning},
file = {Aubret_et_al_2019_Etude_de_la_motivation_intrinseque_en_apprentissage_par_renforcement.pdf:files/6764/Aubret_et_al_2019_Etude_de_la_motivation_intrinseque_en_apprentissage_par_renforcement.pdf:application/pdf},
}
@article{charron_architecture_nodate,
title = {L'architecture fonctionnelle intégrant le contrôle cognitif et le contrôle motivationnel dans le cortex préfrontal humain.},
language = {fr},
author = {Charron, Sylvain},
pages = {196},
file = {Charron_L'architecture_fonctionnelle_integrant_le_controle_cognitif_et_le_controle.pdf:files/6695/Charron_L'architecture_fonctionnelle_integrant_le_controle_cognitif_et_le_controle.pdf:application/pdf},
}
@article{morgagni_repenser_2011,
title = {Repenser la notion d’affordance dans ses dynamiques sémiotiques},
volume = {55},
issn = {0769-4113},
url = {https://www.persee.fr/doc/intel_0769-4113_2011_num_55_1_1170},
doi = {10.3406/intel.2011.1170},
abstract = {Rethinking the Notion of Affordance in its Semiotic Dynamics. As far as semiotic and cognitive theories are concerned, new digital texts and objects emphasize the need to refocus on the intimate connection between user and his environment, considered as a space where cognition emerges, is deployed and manipulated through repeated interactions between subject’s body and the technological and cultural world which surrounds him. In this case, the concept of “affordance” assumes a more central importance. Originally developed in the framework of the Gestalt theory, the notion of Aufforderungscharackter was subsequently reworked and made famous through the notion of affordance integrated in the ecological approach to visual perception conceived by James Gibson. However, the concept has successively been integrated into a more binary conception of cognition, which seems to be responsible for the loss of much of its heuristic power. I intend to go back here to the genesis of the notion and propose a semiotic and dynamic reinterpretation of this concept, where affordances can be seen as dispositions to act and patterns of expectation that are, from the beginning, intrinsically linked to the social and cultural dimensions of the human world. I will show how semiotic activity cannot take place in an infinitely brief presenttime, but needs to be comprehended into a more systemic approach to cognition, where the environment and the subject cannot be considered on the basis of a binary distinction, and where an intrinsically cultural microgenetic activity of perception and cognition is seen as necessary for the emergence of possibilities of action in material and digital objects. In this context, affordances may be explained as responses to a conceivable practical action made possible by habits that subjects consider on the basis of their inclusion into a system of practices and knowledge which foreshadows a specific and situated horizon of action.},
language = {fr},
number = {1},
urldate = {2021-06-22},
journal = {Intellectica. Revue de l'Association pour la Recherche Cognitive},
author = {Morgagni, Simone},
year = {2011},
note = {Number: 1},
pages = {241--267},
file = {Morgagni_2011_Repenser_la_notion_d’affordance_dans_ses_dynamiques_semiotiques.pdf:files/6699/Morgagni_2011_Repenser_la_notion_d’affordance_dans_ses_dynamiques_semiotiques.pdf:application/pdf},
}
@article{le_gall_controexecutif_2009,
title = {Contrôle exécutif, cognition sociale, émotions et métacognition},
volume = {1},
issn = {2101-6739, 2102-6025},
url = {http://www.cairn.info/revue-de-neuropsychologie-2009-1-page-24.htm?ref=doi},
doi = {10.3917/rne.011.0024},
abstract = {RésuméCette synthèse aborde la question de la cognition sociale (théorie de l’esprit en particulier), du traitement des émotions et de la métacognition dans une perspective de neuropsychologie clinique. Nous nous attardons sur les études examinant les relations qu’entretiennent ces différents aspects du comportement humain avec les fonctions exécutives et les structures frontales. Les résultats rapportés montrent que les liens potentiels entre la théorie de l’esprit et le fonctionnement exécutif font encore beaucoup débat, et que l’étude des relations entre théorie de l’esprit et lobe frontal mérite d’être affinée. Les lésions frontales perturbent le traitement des émotions, mais les relations entre perturbation des fonctions exécutives et troubles du traitement des émotions restent inexplorées. La métacognition a été peu étudiée chez les patients dysexécutifs par lésions frontales, si ce n’est au travers de quelques études sur la métamémoire qui montrent que les patients frontaux ont globalement tendance à surestimer leurs performances. Cette surestimation ne semble pas nécessairement procéder d’un déficit exécutif, d’une incapacité de jugement, ni d’une méconnaissance du fonctionnement mnésique normal et pathologique. Il ne s’agit pas non plus d’une difficulté d’utilisation de connaissances. De plus, les différentes mesures métamnésiques obtenues chez les patients frontaux corrèlent peu entre elles, indiquant qu’elles engagent probablement des processus du contrôle métamnésique relativement indépendants qu’il conviendrait de spécifier. Enfin, il faudra aussi vérifier, avec des malades porteurs de lésions frontales et/ou de syndromes dysexécutifs, les propositions théoriques les plus récentes voulant que les concepts de théorie de l’esprit et de métacognition soient finalement assez proches.},
language = {fr},
number = {1},
urldate = {2021-06-22},
journal = {Revue de neuropsychologie},
author = {Le Gall, Didier and Besnard, Jérémy and Havet, Valérie and Pinon, Karine and Allain, Philippe},
year = {2009},
note = {Number: 1},
pages = {24},
file = {Le_Gall_et_al_2009_Controle_executif,_cognition_sociale,_emotions_et_metacognition.pdf:files/6704/Le_Gall_et_al_2009_Controle_executif,_cognition_sociale,_emotions_et_metacognition.pdf:application/pdf},
}
@article{lachaux_eduquer_2018,
title = {Éduquer la métacognition, la clé du succès pour les enfants!},
language = {fr},
author = {Lachaux, Jean-Philippe},
year = {2018},
pages = {3},
file = {Lachaux_2018_Eduquer_la_metacognition,_la_cle_du_succes_pour_les_enfants.pdf:files/6780/Lachaux_2018_Eduquer_la_metacognition,_la_cle_du_succes_pour_les_enfants.pdf:application/pdf},
}
@article{smith_development_1994,
title = {The development of modal understanding: {Piaget}'s possibility and necessity},
volume = {12},
issn = {0732-118X},
shorttitle = {The development of modal understanding},
url = {https://www.sciencedirect.com/science/article/pii/0732118X94900590},
doi = {10.1016/0732-118X(94)90059-0},
abstract = {Possibility and Necessity: The Role of POsssibility in Cognitive Development, Vol. 1 by J. Piaget. Minneapolis, MN: University of Minnesota Press, 1987. (Originally published as Le Possible et le Nécessaire: L'Evolution des Possibles chez L'Enfant. Paris, France: Presses Universitaires de France, 1981.) Possibility and Necessity: The Role of Necessity in Cognitive Development, Vol. 2 by J. Piaget. Minneapolis, MN: University of Minnesota Press, 1987. (Originally published as Le Possible et le Nécessaire: L'Evolution du Necessaire chez l'Enfant. Paris, France: Presses Universitaires de France, 1983.)},
language = {en},
number = {1},
urldate = {2021-07-30},
journal = {New Ideas in Psychology},
author = {Smith, Leslie},
month = mar,
year = {1994},
pages = {73--87},
file = {ScienceDirect Snapshot:files/6874/0732118X94900590.html:text/html;Smith_1994_The_development_of_modal_understanding.pdf:files/6746/Smith_1994_The_development_of_modal_understanding.pdf:application/pdf;The development of modal understanding\: Piaget's possibility and necessity - ScienceDirect:files/6779/0732118X94900590.html:text/html},
}
@article{nguyen-xuan_les_1995,
title = {Les mécanismes cognitifs d'apprentissage},
volume = {112},
copyright = {free},
url = {https://www.persee.fr/doc/rfp_0556-7807_1995_num_112_1_1226},
doi = {10.3406/rfp.1995.1226},
abstract = {Après un bref rappel historique, les trois principaux mécanismes d'apprentissage sont présentés dans le cadre de l'approche « traitement de l'information ». Le premier mécanisme concerne l'apprentissage des concepts à partir des exemples de concepts, le deuxième mécanisme concerne l'apprentissage des connaissances procédurale par la résolution des problèmes, le troisième mécanisme concerne l'apprentissage par analogie. Une discussion est présentée qui tente d'apporter quelques éléments de réflexion sur des questions telles que : l'apprentissage d'un nouveau domaine de connaissance, les différences entre les novices et les experts, la généralisation d'une connaissance apprise.},
language = {fre},
number = {1},
urldate = {2021-07-30},
journal = {Revue française de pédagogie},
author = {Nguyen-Xuan, Anh},
year = {1995},
note = {Publisher: Persée - Portail des revues scientifiques en SHS},
pages = {57--67},
file = {Nguyen-Xuan_1995_Les_mecanismes_cognitifs_d'apprentissage.pdf:files/6738/Nguyen-Xuan_1995_Les_mecanismes_cognitifs_d'apprentissage.pdf:application/pdf;Snapshot:files/6799/rfp_0556-7807_1995_num_112_1_1226.html:text/html},
}
@article{koechlin_evolutionary_2014,
title = {An evolutionary computational theory of prefrontal executive function in decision-making},
volume = {369},
issn = {1471-2970},
doi = {10.1098/rstb.2013.0474},
abstract = {The prefrontal cortex subserves executive control and decision-making, that is, the coordination and selection of thoughts and actions in the service of adaptive behaviour. We present here a computational theory describing the evolution of the prefrontal cortex from rodents to humans as gradually adding new inferential Bayesian capabilities for dealing with a computationally intractable decision problem: exploring and learning new behavioural strategies versus exploiting and adjusting previously learned ones through reinforcement learning (RL). We provide a principled account identifying three inferential steps optimizing this arbitration through the emergence of (i) factual reactive inferences in paralimbic prefrontal regions in rodents; (ii) factual proactive inferences in lateral prefrontal regions in primates and (iii) counterfactual reactive and proactive inferences in human frontopolar regions. The theory clarifies the integration of model-free and model-based RL through the notion of strategy creation. The theory also shows that counterfactual inferences in humans yield to the notion of hypothesis testing, a critical reasoning ability for approximating optimal adaptive processes and presumably endowing humans with a qualitative evolutionary advantage in adaptive behaviour.},
language = {eng},
number = {1655},
journal = {Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences},
author = {Koechlin, Etienne},
month = nov,
year = {2014},
pmid = {25267817},
pmcid = {PMC4186228},
keywords = {Learning, reinforcement learning, Animals, Humans, Models, Neurological, Prefrontal Cortex, decision-making, Executive Function, Reinforcement, Psychology, Rodentia, Decision Making, Bayes Theorem, Bayesian inference, executive control, prefrontal cortex, Primates, Reasoning},
pages = {20130474},
file = {Koechlin_2014_An evolutionary computational theory of prefrontal executive function in.pdf:files/6805/Koechlin_2014_An evolutionary computational theory of prefrontal executive function in.pdf:application/pdf},
}
@phdthesis{khanfir_kallel_mecanismes_2019,
type = {Habilitation à diriger des recherches},
title = {Mécanismes de raisonnement possibiliste pour l'aide à la décision et l'interprétation de scènes},
url = {https://hal.archives-ouvertes.fr/tel-02868499},
urldate = {2021-07-30},
school = {Ecole Nationale des Ingénieurs de Sfax, Université de Sfax},
author = {Khanfir Kallel, Imene},
month = apr,
year = {2019},
keywords = {decision making, interprétation de scène, modeling, modélisation, Possibility theory, prise de décision, scene interpretation},
file = {Khanfir_Kallel_2019_Mecanismes_de_raisonnement_possibiliste_pour_l'aide_a_la_decision_et.pdf:files/6697/Khanfir_Kallel_2019_Mecanismes_de_raisonnement_possibiliste_pour_l'aide_a_la_decision_et.pdf:application/pdf;Mécanismes de raisonnement possibiliste pour l'aide à la décision et l'interprétation de scènes - Archive ouverte HAL:files/6777/tel-02868499.html:text/html},
}
@phdthesis{hoareau_etudes_2017,
type = {phdthesis},
title = {Etudes des mécanismes de maintien en mémoire de travail chez les personnes jeunes et âgées : approches computationnelle et comportementale basées sur les modèles {TBRS}* et {SOB}-{CS}},
shorttitle = {Etudes des mécanismes de maintien en mémoire de travail chez les personnes jeunes et âgées},
url = {https://tel.archives-ouvertes.fr/tel-01746120},
abstract = {La mémoire de travail est un système cognitif essentiel à notre vie quotidienne. Elle nous permet de conserver momentanément des informations dans le but de réaliser une tâche cognitive. Une des caractéristiques principales de ce type de mémoire est d’être limitée en capacité. Les raisons de cette limitation sont largement débattues dans la littérature. Certains modèles considèrent qu'une cause principale de l'oubli en mémoire de travail est l'existence d'un déclin temporel passif de l'activation des représentations mnésiques alors que d'autres modèles supposent que les interférences entre les informations suffisent à expliquer la capacité limitée de cette mémoire. Deux modèles computationnels ont été proposés récemment (TBRS* et SOB-CS) et illustrent parfaitement ce débat. En effet, ils décrivent de manière très différente ce qui se passe au cours d’une tâche de mémoire de travail impliquant à la fois la mémorisation et le traitement d’informations. En plus de s'opposer sur les causes de l’oubli, ils proposent des processus de maintien en mémoire de travail distincts : le rafraîchissement des informations pertinentes selon TBRS* versus la suppression des informations non pertinentes selon SOB-CS. Les travaux de cette thèse se sont organisés autour de deux objectifs principaux. Premièrement, cette thèse a porté sur l’étude de ces deux modèles et leur mécanisme de maintien. Pour cela, nous avons réalisé des expériences comportementales utilisant la tâche d’empan complexe afin de tester des hypothèses précises de ces modèles. Deuxièmement, nous avons étudié, à l'aide des modèles computationnels, les causes des déficits de mémoire de travail observés chez les personnes âgées, dans le but, à long terme, de créer ou d'améliorer les outils de remédiation. Concernant le premier objectif, les différents résultats d’études ont montré une discordance entre le comportement humain et les simulations. En effet, TBRS* et SOB-CS ne permettent pas de reproduire un effet positif du nombre de distracteurs contrairement à ce qui a été observé expérimentalement. Nous proposons que cet effet positif, non prédit par les modèles, est relié à la mémorisation à long terme non prise en compte dans ces deux modèles. Concernant le deuxième objectif, les résultats comportementaux suggèrent que les personnes âgées auraient principalement des difficultés à rafraîchir les traces mnésiques et à stabiliser les informations à long terme au cours d’une tâche d’empan complexe. Dans l’ensemble, les résultats de cette thèse suggèrent d'approfondir les recherches concernant les liens entre les mécanismes de maintien en mémoire de travail et la mémorisation à long terme, par exemple en proposant un nouveau modèle computationnel permettant de rendre compte de nos résultats. Au-delà des avancées concernant la compréhension du fonctionnement de la mémoire de travail, cette thèse montre également que l’utilisation de modèles computationnels revêt un caractère particulièrement pertinent pour l'étude d'une théorie ainsi que pour la comparaison de différentes populations.},
language = {fr},
urldate = {2021-07-30},
school = {Université Grenoble Alpes},
author = {Hoareau, Violette},
month = dec,
year = {2017},
file = {Hoareau_2017_Etudes_des_mecanismes_de_maintien_en_memoire_de_travail_chez_les_personnes.pdf:files/6809/Hoareau_2017_Etudes_des_mecanismes_de_maintien_en_memoire_de_travail_chez_les_personnes.pdf:application/pdf;Snapshot:files/6808/tel-01746120.html:text/html},
}
@inproceedings{modeste_proof_2017,
address = {Dublin, Ireland},
title = {Proof, reasoning and logic at the interface between {Mathematics} and {Computer} {Science} : toward a framework for analyzing problem solving},
shorttitle = {Proof, reasoning and logic at the interface between {Mathematics} and {Computer} {Science}},
url = {https://hal.archives-ouvertes.fr/hal-02398483},
abstract = {After analyzing the relation between mathematics and computer science and the place given to proof, logic and reasoning, we propose and discuss a framework for the study of their interactions based on the ck¢ model. Then, we exemplify this model in the analysis of a problem, making explicit
a mathematical solution and an algorithmic solution.},
urldate = {2021-08-17},
booktitle = {{CERME} 10},
publisher = {DCU Institute of Education},
author = {Modeste, Simon and Beauvoir, Sylvain and Chappelon, Jonathan and Durand-Guerrier, Viviane and León, Nicolás and Meyer, Antoine},
editor = {Dooley, T. and Gueudet, G.},
month = feb,
year = {2017},
keywords = {Mathematics, Computer science, Problem solving, Proof, Reasoning},
pages = {1634--1641},
file = {Modeste_et_al_2017_Proof,_reasoning_and_logic_at_the_interface_between_Mathematics_and_Computer.pdf:files/6814/Modeste_et_al_2017_Proof,_reasoning_and_logic_at_the_interface_between_Mathematics_and_Computer.pdf:application/pdf},
}
@article{sweller_cognitive_1998,
title = {Cognitive {Architecture} and {Instructional} {Design}},
volume = {10},
doi = {10.1023/a:1022193728205},
abstract = {Abstract
Cognitive load theory has been designed to provide guidelines intended to assist in the presentation of information in a manner that encourages learner activities that optimize intellectual performance. The theory assumes a limited capacity working memory that includes partially independent subcomponents to deal with auditory/verbal material and visual/2- or 3-dimensional information as well as an effectively unlimited long-term memory, holding schemas that vary in their degree of automation. These structures and functions of human cognitive architecture have been used to design a variety of novel instructional procedures based on the assumption that working memory load should be reduced and schema construction encouraged. This paper reviews the theory and the instructional designs generated by it.},
journal = {Educational Psychology Review},
author = {Sweller, John and Van Merrienboer, Jeroen J. G. and Paas, Fred},
month = sep,
year = {1998},
pages = {251},
file = {Sweller_et_al_1998_Cognitive_Architecture_and_Instructional_Design.pdf:files/6817/Sweller_et_al_1998_Cognitive_Architecture_and_Instructional_Design.pdf:application/pdf},
}
@article{sweller_cognitive_2019,
title = {Cognitive {Architecture} and {Instructional} {Design}: 20 {Years} {Later}},
volume = {31},
issn = {1573-336X},
shorttitle = {Cognitive {Architecture} and {Instructional} {Design}},
url = {https://doi.org/10.1007/s10648-019-09465-5},
doi = {10.1007/s10648-019-09465-5},
abstract = {Cognitive load theory was introduced in the 1980s as an instructional design theory based on several uncontroversial aspects of human cognitive architecture. Our knowledge of many of the characteristics of working memory, long-term memory and the relations between them had been well-established for many decades prior to the introduction of the theory. Curiously, this knowledge had had a limited impact on the field of instructional design with most instructional design recommendations proceeding as though working memory and long-term memory did not exist. In contrast, cognitive load theory emphasised that all novel information first is processed by a capacity and duration limited working memory and then stored in an unlimited long-term memory for later use. Once information is stored in long-term memory, the capacity and duration limits of working memory disappear transforming our ability to function. By the late 1990s, sufficient data had been collected using the theory to warrant an extended analysis resulting in the publication of Sweller et al. (Educational Psychology Review, 10, 251–296, 1998). Extensive further theoretical and empirical work have been carried out since that time and this paper is an attempt to summarise the last 20 years of cognitive load theory and to sketch directions for future research.},
language = {en},
number = {2},
urldate = {2021-08-23},
journal = {Educational Psychology Review},
author = {Sweller, John and van Merriënboer, Jeroen J. G. and Paas, Fred},
month = jun,
year = {2019},
pages = {261--292},
file = {Sweller_et_al_2019_Cognitive_Architecture_and_Instructional_Design.pdf:files/6820/Sweller_et_al_2019_Cognitive_Architecture_and_Instructional_Design.pdf:application/pdf},
}
@article{sauerwald_random_2019,
title = {Random {Walks} on {Dynamic} {Graphs}: {Mixing} {Times}, {HittingTimes}, and {Return} {Probabilities}},
shorttitle = {Random {Walks} on {Dynamic} {Graphs}},
url = {http://arxiv.org/abs/1903.01342},
abstract = {We establish and generalise several bounds for various random walk quantities including the mixing time and the maximum hitting time. Unlike previous analyses, our derivations are based on rather intuitive notions of local expansion properties which allows us to capture the progress the random walk makes through \$t\$-step probabilities. We apply our framework to dynamically changing graphs, where the set of vertices is fixed while the set of edges changes in each round. For random walks on dynamic connected graphs for which the stationary distribution does not change over time, we show that their behaviour is in a certain sense similar to static graphs. For example, we show that the mixing and hitting times of any sequence of \$d\$-regular connected graphs is \$O(n{\textasciicircum}2)\$, generalising a well-known result for static graphs. We also provide refined bounds depending on the isoperimetric dimension of the graph, matching again known results for static graphs. Finally, we investigate properties of random walks on dynamic graphs that are not always connected: we relate their convergence to stationarity to the spectral properties of an average of transition matrices and provide some examples that demonstrate strong discrepancies between static and dynamic graphs.},
urldate = {2021-09-03},
journal = {arXiv:1903.01342 [cs, math]},
author = {Sauerwald, Thomas and Zanetti, Luca},
month = mar,
year = {2019},
note = {arXiv: 1903.01342},
keywords = {Computer Science - Discrete Mathematics, Mathematics - Probability},
file = {arXiv.org Snapshot:files/6823/1903.html:text/html;Sauerwald_Zanetti_2019_Random Walks on Dynamic Graphs.pdf:files/6822/Sauerwald_Zanetti_2019_Random Walks on Dynamic Graphs.pdf:application/pdf},
}
@article{wang_survey_2021,
title = {A {Survey} on {Knowledge} {Graph} {Embeddings} for {Link} {Prediction}},
volume = {13},
copyright = {http://creativecommons.org/licenses/by/3.0/},
url = {https://www.mdpi.com/2073-8994/13/3/485},
doi = {10.3390/sym13030485},
abstract = {Knowledge graphs (KGs) have been widely used in the field of artificial intelligence, such as in information retrieval, natural language processing, recommendation systems, etc. However, the open nature of KGs often implies that they are incomplete, having self-defects. This creates the need to build a more complete knowledge graph for enhancing the practical utilization of KGs. Link prediction is a fundamental task in knowledge graph completion that utilizes existing relations to infer new relations so as to build a more complete knowledge graph. Numerous methods have been proposed to perform the link-prediction task based on various representation techniques. Among them, KG-embedding models have significantly advanced the state of the art in the past few years. In this paper, we provide a comprehensive survey on KG-embedding models for link prediction in knowledge graphs. We first provide a theoretical analysis and comparison of existing methods proposed to date for generating KG embedding. Then, we investigate several representative models that are classified into five categories. Finally, we conducted experiments on two benchmark datasets to report comprehensive findings and provide some new insights into the strengths and weaknesses of existing models.},
language = {en},
number = {3},
urldate = {2021-09-03},
journal = {Symmetry},
author = {Wang, Meihong and Qiu, Linling and Wang, Xiaoli},
month = mar,
year = {2021},
note = {Number: 3
Publisher: Multidisciplinary Digital Publishing Institute},
keywords = {knowledge graph completion, knowledge graph embedding, link prediction, survey},
pages = {485},
file = {Wang_et_al_2021_A_Survey_on_Knowledge_Graph_Embeddings_for_Link_Prediction.pdf:files/6825/Wang_et_al_2021_A_Survey_on_Knowledge_Graph_Embeddings_for_Link_Prediction.pdf:application/pdf},
}
@inproceedings{guo_jointly_2016,
address = {Austin, Texas},
title = {Jointly {Embedding} {Knowledge} {Graphs} and {Logical} {Rules}},
url = {https://aclanthology.org/D16-1019},
doi = {10.18653/v1/D16-1019},
urldate = {2021-09-03},
booktitle = {Proceedings of the 2016 {Conference} on {Empirical} {Methods} in {Natural} {Language} {Processing}},
publisher = {Association for Computational Linguistics},
author = {Guo, Shu and Wang, Quan and Wang, Lihong and Wang, Bin and Guo, Li},
month = nov,
year = {2016},
pages = {192--202},
file = {Guo_et_al_2016_Jointly_Embedding_Knowledge_Graphs_and_Logical_Rules.pdf:files/6827/Guo_et_al_2016_Jointly_Embedding_Knowledge_Graphs_and_Logical_Rules.pdf:application/pdf},
}
@article{sajjad_efficient_2019,
title = {Efficient {Representation} {Learning} {Using} {Random} {Walks} for {Dynamic} {Graphs}},
url = {http://arxiv.org/abs/1901.01346},
abstract = {An important part of many machine learning workflows on graphs is vertex representation learning, i.e., learning a low-dimensional vector representation for each vertex in the graph. Recently, several powerful techniques for unsupervised representation learning have been demonstrated to give the state-of-the-art performance in downstream tasks such as vertex classification and edge prediction. These techniques rely on random walks performed on the graph in order to capture its structural properties. These structural properties are then encoded in the vector representation space. However, most contemporary representation learning methods only apply to static graphs while real-world graphs are often dynamic and change over time. Static representation learning methods are not able to update the vector representations when the graph changes; therefore, they must re-generate the vector representations on an updated static snapshot of the graph regardless of the extent of the change in the graph. In this work, we propose computationally efficient algorithms for vertex representation learning that extend random walk based methods to dynamic graphs. The computation complexity of our algorithms depends upon the extent and rate of changes (the number of edges changed per update) and on the density of the graph. We empirically evaluate our algorithms on real world datasets for downstream machine learning tasks of multi-class and multi-label vertex classification. The results show that our algorithms can achieve competitive results to the state-of-the-art methods while being computationally efficient.},
urldate = {2021-09-03},
journal = {arXiv:1901.01346 [cs, stat]},
author = {Sajjad, Hooman Peiro and Docherty, Andrew and Tyshetskiy, Yuriy},
month = jan,
year = {2019},
note = {arXiv: 1901.01346},
keywords = {Statistics - Machine Learning, Computer Science - Social and Information Networks, Machine Learning},
file = {arXiv.org Snapshot:files/6830/1901.html:text/html;Sajjad_et_al_2019_Efficient_Representation_Learning_Using_Random_Walks_for_Dynamic_Graphs.pdf:files/6829/Sajjad_et_al_2019_Efficient_Representation_Learning_Using_Random_Walks_for_Dynamic_Graphs.pdf:application/pdf},
}
@article{cohen_tensorlog_2017,
title = {{TensorLog}: {Deep} {Learning} {Meets} {Probabilistic} {DBs}},
shorttitle = {{TensorLog}},
url = {http://arxiv.org/abs/1707.05390},
abstract = {We present an implementation of a probabilistic first-order logic called TensorLog, in which classes of logical queries are compiled into differentiable functions in a neural-network infrastructure such as Tensorflow or Theano. This leads to a close integration of probabilistic logical reasoning with deep-learning infrastructure: in particular, it enables high-performance deep learning frameworks to be used for tuning the parameters of a probabilistic logic. Experimental results show that TensorLog scales to problems involving hundreds of thousands of knowledge-base triples and tens of thousands of examples.},
urldate = {2021-09-03},
journal = {arXiv:1707.05390 [cs]},
author = {Cohen, William W. and Yang, Fan and Mazaitis, Kathryn Rivard},
month = jul,
year = {2017},
note = {arXiv: 1707.05390},
keywords = {Artificial intelligence, I.2.6, I.2.4, Machine Learning},
file = {arXiv.org Snapshot:files/6839/1707.html:text/html;Cohen_et_al_2017_TensorLog.pdf:files/6838/Cohen_et_al_2017_TensorLog.pdf:application/pdf},
}
@inproceedings{mercier_formalizing_2021,
address = {Beijing, China},
title = {Formalizing {Problem} {Solving} in {Computational} {Thinking} : an {Ontology} approach},
shorttitle = {Formalizing {Problem} {Solving} in {Computational} {Thinking}},
doi = {10.1109/ICDL49984.2021.9515660},
abstract = {We introduce the idea of a symbolic description of a complex human learning task, in order to contribute to better understand how we learn. The learner is modeled on the basis of knowledge from learning sciences with the contribution of cognitive neurosciences, including machine learning formalism, in the very precise framework of a task, named \#CreaCube reviewed here, related to initiation to computational thinking presented as an open-ended problem, which involves solving a problem and appealing to creativity. We target problem-solving tasks using tangible interfaces for computational thinking initiation, and describe in details how we model the task and the learner behavior in this task, including goal-driven versus stimulus-driven behavior and the learner knowledge construction. We show how formalizing these elements using an ontology offers a well-defined computational model and the possibility of inferences about model elements, analyzing and predicting the learner behavior. This operationalization of a creative problem-solving task is still at a preliminary stage, but an effective proof of concept is described in this study.},
booktitle = {2021 {IEEE} {International} {Conference} on {Development} and {Learning} ({ICDL})},
author = {Mercier, Chloé and Roux, Lisa and Romero, Margarida and Alexandre, Frédéric and Viéville, Thierry},
month = aug,
year = {2021},
keywords = {Computational thinking, Conferences, Ontology, Ontologies, Machine learning, Computational modelling, Analytical models, Cognitive Neuroscience, Learning Sciences, Predictive models, Problem-solving, Problem-Solving},
pages = {1--8},
file = {IEEE Xplore Abstract Record:files/6843/9515660.html:text/html;Mercier_et_al_2021_Formalizing_Problem_Solving_in_Computational_Thinking.pdf:files/7031/Mercier_et_al_2021_Formalizing_Problem_Solving_in_Computational_Thinking.pdf:application/pdf;Mercier_et_al_2021_Formalizing_Problem_Solving_in_Computational_Thinking.pdf:files/7032/Mercier_et_al_2021_Formalizing_Problem_Solving_in_Computational_Thinking.pdf:application/pdf},
}
@techreport{doriath-dohler_implementation_2021,
type = {Research report},
title = {Implémentation neuronale d’inférences logiques dans une {SPA}},
number = {in preparation},
institution = {Inria Bordeaux Sud-Ouest},
author = {Doriath-Döhler, Gabriel},
year = {2021},
}
@article{bonnefon_machine_2020,
title = {Machine {Thinking}, {Fast} and {Slow}},
volume = {24},
issn = {1364-6613},
url = {https://www.sciencedirect.com/science/article/pii/S1364661320302229},
doi = {10.1016/j.tics.2020.09.007},
abstract = {Machines do not ‘think fast and slow’ in the sense that humans do in dual-process models of cognition. However, the people who create the machines may attempt to emulate or simulate these fast and slow modes of thinking, which will in turn affect the way end users relate to these machines. In this opinion article we consider the complex interplay in the way various stakeholders (engineers, user experience designers, regulators, ethicists, and end users) can be inspired, challenged, or misled by the analogy between the fast and slow thinking of humans and the Fast and Slow Thinking of machines.},
language = {en},
number = {12},
urldate = {2021-10-20},
journal = {Trends in Cognitive Sciences},
author = {Bonnefon, Jean-François and Rahwan, Iyad},
month = dec,
year = {2020},
keywords = {Artificial intelligence, algorithm aversion, dual-process, machine behavior, machine ethics, trust},
pages = {1019--1027},
file = {Bonnefon_Rahwan_2020_Machine_Thinking,_Fast_and_Slow.pdf:files/7036/Bonnefon_Rahwan_2020_Machine_Thinking,_Fast_and_Slow.pdf:application/pdf},
}
@article{rong_word2vec_2016,
title = {word2vec {Parameter} {Learning} {Explained}},
url = {http://arxiv.org/abs/1411.2738},
abstract = {The word2vec model and application by Mikolov et al. have attracted a great amount of attention in recent two years. The vector representations of words learned by word2vec models have been shown to carry semantic meanings and are useful in various NLP tasks. As an increasing number of researchers would like to experiment with word2vec or similar techniques, I notice that there lacks a material that comprehensively explains the parameter learning process of word embedding models in details, thus preventing researchers that are non-experts in neural networks from understanding the working mechanism of such models. This note provides detailed derivations and explanations of the parameter update equations of the word2vec models, including the original continuous bag-of-word (CBOW) and skip-gram (SG) models, as well as advanced optimization techniques, including hierarchical softmax and negative sampling. Intuitive interpretations of the gradient equations are also provided alongside mathematical derivations. In the appendix, a review on the basics of neuron networks and backpropagation is provided. I also created an interactive demo, wevi, to facilitate the intuitive understanding of the model.},
urldate = {2021-11-01},
journal = {arXiv:1411.2738 [cs]},
author = {Rong, Xin},
month = jun,
year = {2016},
note = {arXiv: 1411.2738},
keywords = {Computation and Language},
file = {arXiv.org Snapshot:files/6866/1411.html:text/html;Rong_2016_word2vec Parameter Learning Explained.pdf:files/6865/Rong_2016_word2vec Parameter Learning Explained.pdf:application/pdf},
}
@book{kahneman_thinking_2011,
title = {Thinking, {Fast} and {Slow}},
language = {en},
publisher = {Farrar, Straus and Giroux},
author = {Kahneman, Daniel},
year = {2011},
file = {Snapshot:files/6868/thinking-fast-and-slow-summary-daniel-kahneman.html:text/html},
}
@article{netzer_real_2016,
title = {Real {Algebraic} {Geometry} and its {Applications}},
url = {http://arxiv.org/abs/1606.07284},
abstract = {This is a survey article on real algebra and geometry, and in particular on its recent applications in optimization and convexity. We first introduce basic notions and results from the classical theory. We then explain how these relate to optimization, mostly via semidefinite programming. We introduce interesting geometric problems arising from the classification of feasible sets for semidefinite programming. We close with a perspective on the very active area of non-commutative real algebra and geometry.},
urldate = {2021-11-04},
journal = {arXiv:1606.07284 [math]},
author = {Netzer, Tim},
month = jun,
year = {2016},
note = {arXiv: 1606.07284},
keywords = {Mathematics - Algebraic Geometry, Mathematics - Optimization and Control},
annote = {Comment: This is a review article, to appear in "Internationale Mathematische Nachrichten" (journal of the Austrian Mathematical Society)},
file = {arXiv.org Snapshot:files/6872/1606.html:text/html;Netzer_2016_Real Algebraic Geometry and its Applications.pdf:files/6871/Netzer_2016_Real Algebraic Geometry and its Applications.pdf:application/pdf},
}
@misc{fischer_modal_2018,
title = {Modal {Epistemology}: {Knowledge} of {Possibility} \& {Necessity}},
shorttitle = {Modal {Epistemology}},
url = {https://1000wordphilosophy.com/2018/02/13/modal-epistemology/},
abstract = {Author: Bob Fischer Categories: Epistemology, Metaphysics Word Count: 998 Alice hits Betty, and Betty gets mad. Is her anger justified? Betty thinks so. After all, Alice didn’t need to hit her; Ali…},
language = {en},
urldate = {2021-11-07},
journal = {1000-Word Philosophy: An Introductory Anthology},
author = {Fischer, Bob},
month = feb,
year = {2018},
file = {Snapshot:files/6876/modal-epistemology.html:text/html},
}
@article{beynon_dempstershafer_2000,
title = {The {Dempster}–{Shafer} theory of evidence: an alternative approach to multicriteria decision modelling},
volume = {28},
issn = {0305-0483},
shorttitle = {The {Dempster}–{Shafer} theory of evidence},
url = {https://www.sciencedirect.com/science/article/pii/S030504839900033X},
doi = {10.1016/S0305-0483(99)00033-X},
abstract = {The objective of this paper is to describe the potential offered by the Dempster–Shafer theory (DST) of evidence as a promising improvement on “traditional” approaches to decision analysis. Dempster–Shafer techniques originated in the work of Dempster on the use of probabilities with upper and lower bounds. They have subsequently been popularised in the literature on Artificial Intelligence (AI) and Expert Systems, with particular emphasis placed on combining evidence from different sources. In the paper we introduce the basic concepts of the DST of evidence, briefly mentioning its origins and comparisons with the more traditional Bayesian theory. Following this we discuss recent developments of this theory including analytical and application areas of interest. Finally we discuss developments via the use of an example incorporating DST with the Analytic Hierarchy Process (AHP).},
language = {en},
number = {1},
urldate = {2021-11-07},
journal = {Omega},
author = {Beynon, Malcolm and Curry, Bruce and Morgan, Peter},
month = feb,
year = {2000},
keywords = {AHP, Dempster–Shafer theory, Evidence theory, Multicriteria decision making, Probabilities, Belief function},
pages = {37--50},
file = {Beynon_et_al_2000_The_Dempster–Shafer_theory_of_evidence.pdf:files/7038/Beynon_et_al_2000_The_Dempster–Shafer_theory_of_evidence.pdf:application/pdf;ScienceDirect Snapshot:files/6878/S030504839900033X.html:text/html},
}
@book{riley_computational_2014,
title = {Computational {Thinking} for the {Modern} {Problem} {Solver}},
isbn = {978-1-4665-8777-9},
abstract = {Through examples and analogies, Computational Thinking for the Modern Problem Solver introduces computational thinking as part of an introductory computing course and shows how computer science concepts are applicable to other fields. It keeps the material accessible and relevant to noncomputer science majors. With numerous color figures, this classroom-tested book focuses on both foundational computer science concepts and engineering topics. It covers abstraction, algorithms, logic, graph theory, social issues of software, and numeric modeling as well as execution control, problem-solving strategies, testing, and data encoding and organizing. The text also discusses fundamental concepts of programming, including variables and assignment, sequential execution, selection, repetition, control abstraction, data organization, and concurrency. The authors present the algorithms using language-independent notation.},
language = {en},
publisher = {CRC Press},
author = {Riley, David D. and Hunt, Kenny A.},
month = mar,
year = {2014},
note = {Google-Books-ID: 7AQNAwAAQBAJ},
keywords = {Mathematics / General, Computers / General, Computers / Programming / Algorithms, Mathematics / Advanced, Mathematics / Arithmetic},
}
@phdthesis{borghesani_neuro-cognitive_2017,
type = {phdthesis},
title = {The neuro-cognitive representation of word meaning resolved in space and time},
url = {https://tel.archives-ouvertes.fr/tel-02054668},
abstract = {One of the core human abilities is that of interpreting symbols. Notwithstanding decades of neuropsychological and neuroimaging work on the cognitive and neural substrate of semantic representations, many questions are left unanswered. The research in this dissertation attempts to unravel one of them: are the neural substrates of different components of concrete word meaning dissociated? In the first part, I review the different theoretical positions and empirical findings on the cognitive and neural correlates of semantic representations. Crucially, I propose an operational distinction between motor-perceptual dimensions (i.e., those attributes of the objects referred to by the words that are perceived through the senses) and conceptual ones (i.e., the information that is built via a complex integration of multiple perceptual features). In the second part, I present the results of the studies I conducted in order to investigate the automaticity of retrieval, topographical organization, and temporal dynamics of motor-perceptual and conceptual dimensions of word meaning. The results suggest that the neural substrates of different components of symbol meaning can be dissociated in terms of localization and of the feature of the signal encoding them, while sharing a similar temporal evolution.},
language = {en},
urldate = {2021-11-12},
school = {Université Pierre et Marie Curie - Paris VI ; Università degli studi (Trente, Italie)},
author = {Borghesani, Valentina},
month = feb,
year = {2017},
file = {Borghesani_2017_The_neuro-cognitive_representation_of_word_meaning_resolved_in_space_and_time.pdf:files/6882/Borghesani_2017_The_neuro-cognitive_representation_of_word_meaning_resolved_in_space_and_time.pdf:application/pdf;Snapshot:files/6883/tel-02054668.html:text/html},
}
@article{taddeo_solving_2005,
title = {Solving the {Symbol} {Grounding} {Problem}: {A} {Critical} {Review} of {Fifteen} {Years} of {Research}},
volume = {17},
shorttitle = {Solving the {Symbol} {Grounding} {Problem}},
doi = {10.1080/09528130500284053},
abstract = {This article reviews eight proposed strategies for solving the Symbol Grounding Problem (SGP), which was given its classic formulation in Harnad (1990). After a concise introduction, we provide an analysis of the requirement that must be satisfied by any hypothesis seeking to solve the SGP, the zero semantical commitment condition. We then use it to assess the eight strategies, which are organised into three main approaches: representationalism, semi-representationalism and non-representationalism. The conclusion is that all the strategies are semantically committed and hence that none of them provides a valid solution to the SGP, which remains an open problem.},
journal = {Journal of Experimental and Theoretical Artificial Intelligence},
author = {Taddeo, Mariarosaria and Floridi, Luciano},
month = dec,
year = {2005},
file = {Taddeo_Floridi_2005_Solving the Symbol Grounding Problem.pdf:files/6885/Taddeo_Floridi_2005_Solving the Symbol Grounding Problem.pdf:application/pdf},
}
@article{shleifer_psychologists_2012,
title = {Psychologists at the {Gate}: {A} {Review} of {Daniel} {Kahneman}\&\#039;s \<em\>{Thinking}, {Fast} and {Slow}\</em\>},
volume = {50},
issn = {0022-0515},
shorttitle = {Psychologists at the {Gate}},
url = {https://www.aeaweb.org/articles?id=10.1257/jel.50.4.1080},
doi = {10.1257/jel.50.4.1080},
abstract = {Psychologists at the Gate: A Review of Daniel Kahneman's Thinking, Fast and Slow by Andrei Shleifer. Published in volume 50, issue 4, pages 1080-91 of Journal of Economic Literature, December 2012, Abstract: The publication of Daniel Kahneman's book, Thinking, Fast and Slow, is a major intellectual...},
language = {en},
number = {4},
urldate = {2021-11-12},
journal = {Journal of Economic Literature},
author = {Shleifer, Andrei},
month = dec,
year = {2012},
pages = {1080--91},
file = {Shleifer_2012_Psychologists at the Gate.pdf:files/6890/Shleifer_2012_Psychologists at the Gate.pdf:application/pdf;Snapshot:files/6891/articles.html:text/html},
}
@article{harnad_symbol_1990,
title = {The symbol grounding problem},
volume = {42},
issn = {0167-2789},
url = {https://www.sciencedirect.com/science/article/pii/0167278990900876},
doi = {10.1016/0167-2789(90)90087-6},
abstract = {There has been much discussion recently about the scope and limits of purely symbolic models of the mind and about the proper role of connectionism in cognitive modeling. This paper describes the “symbol grounding problem”: How can the semantic interpretation of a formal symbol system be made intrinsic to the system, rather than just parasitic on the meanings in our heads? How can the meanings of the meaningless symbol tokens, manipulated solely on the basis of their (arbitrary) shapes, be grounded in anything but other meaningless symbols? The problem is analogous to trying to learn Chinese from a Chinese/Chinese dictionary alone. A candidate solution is sketched: Symbolic representations must be grounded bottom-up in nonsymbolic representations of two kinds: (1) iconic representations, which are analogs of the proximal sensory projections of distal objects and events, and (2) categorical representations, which are learned and innate feature detectors that pick out the invariant features of object and event categories from their sensory projections. Elementary symbols are the names of these object and event categories, assigned on the basis of their (nonsymbolic) categorical representations. Higher-order (3) symbolic representations, grounded in these elementary symbols, consist of symbol strings describing category membership relations (e.g. “An X is a Y that is Z”). Connectionism is one natural candidate for the mechanism that learns the invariant features underlying categorical representations, thereby connecting names to the proximal projections of the distal objects they stand for. In this way connectionism can be seen as a complementary component in a hybrid nonsymbolic/symbolic model of the mind, rather than a rival to purely symbolic modeling. Such a hybrid model would not have an autonomous symbolic “module,” however; the symbolic functions would emerge as an intrinsically “dedicated” symbol system as a consequence of the bottom-up grounding of categories' names in their sensory representations. Symbol manipulation would be governed not just by the arbitrary shapes of the symbol tokens, but by the nonarbitrary shapes of the icons and category invariants in which they are grounded.},
language = {en},
number = {1},
urldate = {2021-11-12},
journal = {Physica D: Nonlinear Phenomena},
author = {Harnad, Stevan},
month = jun,
year = {1990},
pages = {335--346},
file = {Harnad_1990_The symbol grounding problem.pdf:files/6894/Harnad_1990_The symbol grounding problem.pdf:application/pdf;ScienceDirect Snapshot:files/6893/0167278990900876.html:text/html},
}
@article{davis_commonsense_2015,
title = {Commonsense reasoning and commonsense knowledge in artificial intelligence},
volume = {58},
issn = {0001-0782, 1557-7317},
url = {https://dl.acm.org/doi/10.1145/2701413},
doi = {10.1145/2701413},
abstract = {Since the earliest days of artificial intelligence, it has been recognized that commonsense reasoning is one of the central challenges in the field. However, progress in this area has on the whole been frustratingly slow. In this review paper, we discuss why commonsense reasoning is needed to achieve human-level performance in tasks like natural language processing, vision, and robotics, why the problem is so difficult, and why progress has been slow. We also discuss four particular areas where substantial progress has been made, the techniques that have been attempted, and prospects for going forward.},
language = {en},
number = {9},
urldate = {2021-11-18},
journal = {Communications of the ACM},
author = {Davis, Ernest and Marcus, Gary},
month = aug,
year = {2015},
pages = {92--103},
file = {Davis_Marcus_2015_Commonsense_reasoning_and_commonsense_knowledge_in_artificial_intelligence.pdf:files/6924/Davis_Marcus_2015_Commonsense_reasoning_and_commonsense_knowledge_in_artificial_intelligence.pdf:application/pdf},
}
@article{gordon_formalizations_2004,
title = {Formalizations of {Commonsense} {Psychology}},
volume = {25},
copyright = {Copyright (c)},
issn = {2371-9621},
url = {https://ojs.aaai.org/index.php/aimagazine/article/view/1784},
doi = {10.1609/aimag.v25i4.1784},
abstract = {The central challenge in commonsense knowledge representation research is to develop content theories that achieve a high degree of both competency and coverage. We describe a new methodology for constructing formal theories in commonsense knowledge domains that complements traditional knowledge representation approaches by first addressing issues of coverage. We show how a close examination of a very general task (strategic planning) leads to a catalog of the concepts and facts that must be encoded for general commonsense reasoning. These concepts are sorted into a manageable number of coherent domains, one of which is the representational area of commonsense human memory. We then elaborate on these concepts using textual corpus-analysis techniques, where the conceptual distinctions made in natural language are used to improve the definitions of the concepts that should be expressible in our formal theories. These representational areas are then analyzed using more traditional knowledge representation techniques, as demonstrated in this article by our treatment of commonsense human memory.},
language = {en},
number = {4},
urldate = {2021-11-16},
journal = {AI Magazine},
author = {Gordon, Andrew S. and Hobbs, Jerry R.},
month = dec,
year = {2004},
note = {Number: 4},
pages = {49--49},
file = {Gordon_Hobbs_2004_Formalizations_of_Commonsense_Psychology.pdf:files/6925/Gordon_Hobbs_2004_Formalizations_of_Commonsense_Psychology.pdf:application/pdf},
}
@article{st_b_t_evans_reasoning_1999,
title = {Reasoning about necessity and possibility: {A} test of the mental model theory of deduction},
volume = {25},
issn = {1939-1285},
shorttitle = {Reasoning about necessity and possibility},
doi = {10.1037/0278-7393.25.6.1495},
abstract = {This article examined syllogistic reasoning in college students that differs from previous research in 2 significant ways: (a) Participants were asked to decide whether conclusions were possible as well as necessary, and (b) every possible combination of syllogistic premises and conclusions was presented for evaluation with both single-premise (Experiment 1) and double-premise (Experiment 2) problems. Participants more frequently endorsed conclusions as possible than as necessary, and differences in response to the 2 forms of instruction conformed to several predictions derived from the mental model theory of deduction. Findings of Experiments 2 and 3 showed that some fallacies are consistently endorsed and others consistently resisted when people are asked to judge whether conclusions that are only possible follow necessarily. This finding was accounted for by the computational implementation of the model theory: Fallacies are made when the first mental model of the premises considered supports the conclusion presented. (PsycINFO Database Record (c) 2016 APA, all rights reserved)},
number = {6},
journal = {Journal of Experimental Psychology: Learning, Memory, and Cognition},
author = {St. B. T. Evans, Jonathan and Handley, Simon J. and Harper, Catherine N. J. and Johnson-Laird, Phillip N.},
year = {1999},
note = {Place: US
Publisher: American Psychological Association},
keywords = {Models, Inductive Deductive Reasoning, Mental Models, Theory Verification},
pages = {1495--1513},
file = {Snapshot:files/6927/1999-01477-009.html:text/html;St._B._T._Evans_et_al_1999_Reasoning_about_necessity_and_possibility.pdf:files/7518/St._B._T._Evans_et_al_1999_Reasoning_about_necessity_and_possibility.pdf:application/pdf},
}
@article{johnson-laird_possibilities_2019,
title = {Possibilities as the foundation of reasoning},
volume = {193},
issn = {00100277},
url = {https://linkinghub.elsevier.com/retrieve/pii/S0010027719301039},
doi = {10.1016/j.cognition.2019.04.019},
abstract = {Reasoning about possibilities is fundamental in daily life. Yet, it has been little studied in psychology. We present a psychological theory in which it is the foundation of human reasoning. The theory explains how possibilities have distinct interpretations (deontic, epistemic, and alethic), how people represent them in models, and how these models yield inferences. Key principles are that the semantics of possibilities are the same finitary alternatives underlying probabilities, that speech acts can create obligations inexpressible as probabilities, that compound assertions – conditionals and disjunctions – refer to conjunctions of possibilities holding in default of knowledge to the contrary, and that mental models condense multiple consistent possibilities into one. The theory is incompatible with all normal modal logics and with probabilistic logic. Yet, experiments have corroborated its predictions. The article discusses its precursors, rivals, and potentials.},
language = {en},
urldate = {2021-11-17},
journal = {Cognition},
author = {Johnson-Laird, P.N. and Ragni, Marco},
month = dec,
year = {2019},
pages = {103950},
file = {Johnson-Laird_Ragni_2019_Possibilities_as_the_foundation_of_reasoning.pdf:files/6928/Johnson-Laird_Ragni_2019_Possibilities_as_the_foundation_of_reasoning.pdf:application/pdf},
}
@article{oaksford_precis_2009,
title = {Précis of {Bayesian} {Rationality}: {The} {Probabilistic} {Approach} to {Human} {Reasoning}},
volume = {32},
issn = {0140-525X, 1469-1825},
shorttitle = {Précis of {\textless}i{\textgreater}{Bayesian} {Rationality}},
url = {https://www.cambridge.org/core/product/identifier/S0140525X09000284/type/journal_article},
doi = {10.1017/S0140525X09000284},
abstract = {According to Aristotle, humans are the rational animal. The borderline between rationality and irrationality is fundamental to many aspects of human life including the law, mental health, and language interpretation. But what is it to be rational? One answer, deeply embedded in the Western intellectual tradition since ancient Greece, is that rationality concerns reasoning according to the rules of logic – the formal theory that specifies the inferential connections that hold with certainty between propositions. Piaget viewed logical reasoning as defining the end-point of cognitive development; and contemporary psychology of reasoning has focussed on comparing human reasoning against logical standards.},
language = {en},
number = {1},
urldate = {2021-11-17},
journal = {Behavioral and Brain Sciences},
author = {Oaksford, Mike and Chater, Nick},
month = feb,
year = {2009},
pages = {69--84},
file = {Oaksford_Chater_2009_Precis_of_Bayesian_Rationality.pdf:files/6929/Oaksford_Chater_2009_Precis_of_Bayesian_Rationality.pdf:application/pdf},
}
@article{khemlani_causal_2014,
title = {Causal reasoning with mental models},
volume = {8},
issn = {1662-5161},
url = {http://journal.frontiersin.org/article/10.3389/fnhum.2014.00849/abstract},
doi = {10.3389/fnhum.2014.00849},
abstract = {This paper outlines the model-based theory of causal reasoning. It postulates that the core meanings of causal assertions are deterministic and refer to temporally-ordered sets of possibilities: A causes B to occur means that given A, B occurs, whereas A enables B to occur means that given A, it is possible for B to occur. The paper shows how mental models represent such assertions, and how these models underlie deductive, inductive, and abductive reasoning yielding explanations. It reviews evidence both to corroborate the theory and to account for phenomena sometimes taken to be incompatible with it. Finally, it reviews neuroscience evidence indicating that mental models for causal inference are implemented within lateral prefrontal cortex.},
language = {en},
urldate = {2021-11-18},
journal = {Frontiers in Human Neuroscience},
author = {Khemlani, Sangeet S. and Barbey, Aron K. and Johnson-Laird, Philip N.},
month = oct,
year = {2014},
file = {Khemlani_et_al_2014_Causal_reasoning_with_mental_models.pdf:files/6932/Khemlani_et_al_2014_Causal_reasoning_with_mental_models.pdf:application/pdf},
}
@article{khemlani_naive_2015,
title = {Naive probability: {Model}‐based estimates of unique events},
volume = {39},
issn = {1551-6709},
shorttitle = {Naive probability},
doi = {10.1111/cogs.12193},
abstract = {We describe a dual‐process theory of how individuals estimate the probabilities of unique events, such as Hillary Clinton becoming U.S. President. It postulates that uncertainty is a guide to improbability. In its computer implementation, an intuitive system 1 simulates evidence in mental models and forms analog non‐numerical representations of the magnitude of degrees of belief. This system has minimal computational power and combines evidence using a small repertoire of primitive operations. It resolves the uncertainty of divergent evidence for single events, for conjunctions of events, and for inclusive disjunctions of events, by taking a primitive average of non‐numerical probabilities. It computes conditional probabilities in a tractable way, treating the given event as evidence that may be relevant to the probability of the dependent event. A deliberative system 2 maps the resulting representations into numerical probabilities. With access to working memory, it carries out arithmetical operations in combining numerical estimates. Experiments corroborated the theory's predictions. Participants concurred in estimates of real possibilities. They violated the complete joint probability distribution in the predicted ways, when they made estimates about conjunctions: P(A), P(B), P(A and B), disjunctions: P(A), P(B), P(A or B or both), and conditional probabilities P(A), P(B), P(B{\textbar}A). They were faster to estimate the probabilities of compound propositions when they had already estimated the probabilities of each of their components. We discuss the implications of these results for theories of probabilistic reasoning. (PsycINFO Database Record (c) 2016 APA, all rights reserved)},
number = {6},
journal = {Cognitive Science},
author = {Khemlani, Sangeet S. and Lotstein, Max and Johnson‐Laird, Philip N.},
year = {2015},
note = {Place: United Kingdom
Publisher: Wiley-Blackwell Publishing Ltd.},
keywords = {Decision Making, Cognitive Processes, Mental Models, Probability, Probability Judgment, Uncertainty},
pages = {1216--1258},
file = {Khemlani_et_al_2015_Naive_probability.pdf:files/6934/Khemlani_et_al_2015_Naive_probability.pdf:application/pdf;Snapshot:files/6933/2015-34428-004.html:text/html},
}
@article{ragni_reasoning_2018,
title = {Reasoning about possibilities: human reasoning violates all normal modal logics},
abstract = {Reasoning about possibilities is fundamental in daily life and in artificial intelligence. It is formalized in modal logics, of which there are infinitely many. Two experiments showed that individuals make inferences that are parsimonious about possibilities, and that they reject conclusions referring to possibilities that the premises do not support. Both sorts of inference contravene modal logics, i.e., the simplest system of modal logic and the infinite number of systems based on it.},
language = {en},
journal = {CogSci},
author = {Ragni, Marco and Johnson-Laird, P N},
year = {2018},
pages = {6},
file = {Ragni_Johnson-Laird_2018_Reasoning_about_possibilities.pdf:files/6937/Ragni_Johnson-Laird_2018_Reasoning_about_possibilities.pdf:application/pdf},
}
@article{hutchins_direct_nodate,
title = {Direct {Manipulation} {Interfaces}},
abstract = {Direct manipulation has been lauded as a good form of interface design, and some interfaces that have this property have been well received by users. In this article we seek a cognitive account of both the advantages and disadvantages of direct manipulation interfaces. We identify two underlying phenomena that give rise to the feeling of directness. O n e deals with the information processing distance between the user’s intentions and the facilities provided by the machine. Reduction of this distance makes the interface feel direct by reducing the effort required of the user to accomplish goals. The second phenomenon concerns the relation between the input and output vocabularies of the interface language. In particular, direct manipulation requires that the system provide representations of objects that behave as if they are the objects themselves. This provides the feeling of directness of manipulation.},
language = {en},
author = {Hutchins, Edwin L and Hollan, James D and Norman, Donald A},
pages = {28},
file = {Hutchins_et_al_Direct_Manipulation_Interfaces.pdf:files/6938/Hutchins_et_al_Direct_Manipulation_Interfaces.pdf:application/pdf},
}
@article{rezgui_ontology-based_2014,
title = {An {Ontology}-based {Profile} for {Learner} {Representation} in {Learning} {Networks}},
volume = {9},
issn = {1863-0383},
url = {https://online-journals.org/index.php/i-jet/article/view/3305},
doi = {10.3991/ijet.v9i3.3305},
abstract = {In the context of lifelong learning, learning networks are emerged as alternative and feasible integrated models that merge pedagogical, organizational, and technological perspectives to support and promote the provision of lifelong learning opportunities. Among the significant issues that arise when setting up a learning network is the question of how to support communication between repositories that employ different schemes for describing learner profiles. To guarantee correct interpretation, a semantic common metadata schema is required. This paper aims to propose an ontological structure for representing a learner profile that augments it with semantics and provides a common vocabulary for the exchange of the different learner's characteristics that can be presented in a learner model. The proposed structure is based on different learner information with respect to well-known learner model specifications. Besides, it reuses terms from well-developed Semantic Web vocabularies which make it semantic web compliant and integrates different domain taxonomies and subject taxonomies that are used as ranges for particular concepts' slots.},
language = {en},
number = {3},
urldate = {2021-10-05},
journal = {International Journal of Emerging Technologies in Learning (iJET)},
author = {Rezgui, Kalthoum and Mhiri, Hédia and Ghédira, Khaled},
month = may,
year = {2014},
pages = {16},
file = {Rezgui_et_al_2014_An_Ontology-based_Profile_for_Learner_Representation_in_Learning_Networks.pdf:files/6944/Rezgui_et_al_2014_An_Ontology-based_Profile_for_Learner_Representation_in_Learning_Networks.pdf:application/pdf},
}
@article{lake_building_2017,
title = {Building machines that learn and think like people},
volume = {40},
issn = {0140-525X, 1469-1825},
url = {https://www.cambridge.org/core/product/identifier/S0140525X16001837/type/journal_article},
doi = {10.1017/S0140525X16001837},
abstract = {Recent progress in artificial intelligence has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats that of humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. We review progress in cognitive science suggesting that truly human-like learning and thinking machines will have to reach beyond current engineering trends in both what they learn and how they learn it. Specifically, we argue that these machines should (1) build causal models of the world that support explanation and understanding, rather than merely solving pattern recognition problems; (2) ground learning in intuitive theories of physics and psychology to support and enrich the knowledge that is learned; and (3) harness compositionality and learning-to-learn to rapidly acquire and generalize knowledge to new tasks and situations. We suggest concrete challenges and promising routes toward these goals that can combine the strengths of recent neural network advances with more structured cognitive models.},
language = {en},
urldate = {2021-11-01},
journal = {Behavioral and Brain Sciences},
author = {Lake, Brenden M. and Ullman, Tomer D. and Tenenbaum, Joshua B. and Gershman, Samuel J.},
year = {2017},
pages = {e253},
file = {Lake_et_al_2017_Building_machines_that_learn_and_think_like_people.pdf:files/6940/Lake_et_al_2017_Building_machines_that_learn_and_think_like_people.pdf:application/pdf},
}
@inproceedings{varadarajan_afnet_2013,
address = {Berlin, Heidelberg},
series = {Lecture {Notes} in {Computer} {Science}},
title = {{AfNet}: {The} {Affordance} {Network}},
isbn = {978-3-642-37331-2},
shorttitle = {{AfNet}},
doi = {10.1007/978-3-642-37331-2_39},
abstract = {There has been a growing need to build an object recognition system that can successfully characterize object constancy, irrespective of lighting, shading, occlusions, viewpoint variations and most importantly, deal with the multitude of shapes, colors and sizes in which objects are found. Affordances on the other hand, provide symbolic grounding mechanisms that enable linking features obtained from visual perception with the functionality of the objects, which provides the most consistent and holistic characterization of an object. Recognition by Component Affordances (RBCA) is a recent theory that builds affordance features for recognition. As an extension of the psychophysical theory of Recognition by Components (RBC) to generic visual perception, RBCA is well suited for cognitive visual processing systems which are required to perform implicit cognitive tasks. A common task is to substitute a cup for a mug, bottle, jug, pitcher, pilsner, beaker, chalice, goblet or any other unlabeled object, but with a physical part affording the ability to hold liquid and a part affording grasping by a human hand, given the goal of ’finding an empty cup’ and no cups are available in the work environment of interest. In this paper, we present affordance features for recognition of objects. Using a set of 25 structural and 10 material affordances we define a database of over 250 common household objects. This database called the Affordance Network or AfNet is available as community development framework and is well suited for deployment on domestic robots. Sample object recognition results using AfNet and the associated inference engine that grounds the affordances through visual perception features demonstrate the effectiveness of the approach.},
language = {en},
booktitle = {Computer {Vision} – {ACCV} 2012},
publisher = {Springer},
author = {Varadarajan, Karthik Mahesh and Vincze, Markus},
editor = {Lee, Kyoung Mu and Matsushita, Yasuyuki and Rehg, James M. and Hu, Zhanyi},
year = {2013},
keywords = {Inference Engine, Object Recognition, Object Recognition System, Range Image, Symbol Grounding},
pages = {512--523},
file = {AfNet 2.0\: The Affordance Network:files/6941/getaffordances.html:text/html;Varadarajan_Vincze_2013_AfNet.pdf:files/6942/Varadarajan_Vincze_2013_AfNet.pdf:application/pdf},
}
@misc{noauthor_survey_nodate,
title = {A {Survey} of {Ontologies} and {Their} {Applications} in e-{Learning} {Environments} {\textbar} www.semantic-web-journal.net},
url = {http://www.semantic-web-journal.net/content/survey-ontologies-and-their-applications-e-learning-environments},
urldate = {2021-10-05},
file = {A Survey of Ontologies and Their Applications in e-Learning Environments | www.semantic-web-journal.net:files/6945/survey-ontologies-and-their-applications-e-learning-environments.html:text/html},
}
@article{kurilovas_creation_2015,
title = {Creation of {Web} 2.0 tools ontology to improve learning},
volume = {51},
issn = {07475632},
url = {https://linkinghub.elsevier.com/retrieve/pii/S0747563214005494},
doi = {10.1016/j.chb.2014.10.026},
language = {en},
urldate = {2021-10-05},
journal = {Computers in Human Behavior},
author = {Kurilovas, Eugenijus and Juskeviciene, Anita},
month = oct,
year = {2015},
pages = {1380--1386},
file = {Kurilovas_Juskeviciene_2015_Creation_of_Web_2.pdf:files/6947/Kurilovas_Juskeviciene_2015_Creation_of_Web_2.pdf:application/pdf},
}
@article{kotseruba_review_2016,
title = {A {Review} of 40 {Years} of {Cognitive} {Architecture} {Research}: {Focus} on {Perception}, {Attention}, {Learning} and {Applications}},
shorttitle = {A {Review} of 40 {Years} of {Cognitive} {Architecture} {Research}},
abstract = {In this paper we present a broad overview of the last 40 years of research on cognitive architectures. Although the number of existing architectures is nearing several hundred, most of the existing surveys do not reflect this growth and focus on a handful of well-established architectures. While their contributions are undeniable, they represent only a part of the research in the field. Thus, in this survey we wanted to shift the focus towards a more inclusive and high-level overview of the research in cognitive architectures. Our final set of 86 architectures includes 55 that are still actively developed, and borrow from a diverse set of disciplines, spanning areas from psychoanalysis to neuroscience. To keep the length of this paper within reasonable limits we discuss only the core cognitive abilities, such as perception, attention mechanisms, learning and memory structure. To assess the breadth of practical applications of cognitive architectures we gathered information on over 700 practical projects implemented using the cognitive architectures in our list. We use various visualization techniques to highlight overall trends in the development of the field. Our analysis of practical applications shows that most architectures are very narrowly focused on a particular application domain. Furthermore, there is an apparent gap between general research in robotics and computer vision and research in these areas within the cognitive architectures field. It is very clear that biologically inspired models do not have the same range and efficiency compared to the systems based on engineering principles and heuristics. Another observation is related to a general lack of collaboration. Several factors hinder communication, such as the closed nature of the individual projects (only one-third of the reviewed here architectures are open-source) and terminological differences.},
author = {Kotseruba, Yulia and Avella, Oscar and Tsotsos, John},
month = oct,
year = {2016},
file = {Kotseruba_et_al_2016_A_Review_of_40_Years_of_Cognitive_Architecture_Research.pdf:files/6948/Kotseruba_et_al_2016_A_Review_of_40_Years_of_Cognitive_Architecture_Research.pdf:application/pdf},
}
@article{johnson-laird_naive_1999,
title = {Naive probability: a mental model theory of extensional reasoning},
volume = {106},
issn = {0033-295X},
shorttitle = {Naive probability},
doi = {10.1037/0033-295x.106.1.62},
abstract = {This article outlines a theory of naive probability. According to the theory, individuals who are unfamiliar with the probability calculus can infer the probabilities of events in an extensional way: They construct mental models of what is true in the various possibilities. Each model represents an equiprobable alternative unless individuals have beliefs to the contrary, in which case some models will have higher probabilities than others. The probability of an event depends on the proportion of models in which it occurs. The theory predicts several phenomena of reasoning about absolute probabilities, including typical biases. It correctly predicts certain cognitive illusions in inferences about relative probabilities. It accommodates reasoning based on numerical premises, and it explains how naive reasoners can infer posterior probabilities without relying on Bayes's theorem. Finally, it dispels some common misconceptions of probabilistic reasoning.},
language = {eng},
number = {1},
journal = {Psychological Review},
author = {Johnson-Laird, P. N. and Legrenzi, P. and Girotto, V. and Legrenzi, M. S. and Caverni, J. P.},
month = jan,
year = {1999},
pmid = {10197363},
keywords = {Humans, Cognition, Models, Psychological, Decision Making, Probability Theory},
pages = {62--88},
file = {Johnson-Laird_et_al_1999_Naive_probability.pdf:files/6955/Johnson-Laird_et_al_1999_Naive_probability.pdf:application/pdf},
}
@article{boden_creativity_1998,
series = {Artificial {Intelligence} 40 years later},
title = {Creativity and artificial intelligence},
volume = {103},
issn = {0004-3702},
url = {https://www.sciencedirect.com/science/article/pii/S0004370298000551},
doi = {10.1016/S0004-3702(98)00055-1},
abstract = {Creativity is a fundamental feature of human intelligence, and a challenge for AI. AI techniques can be used to create new ideas in three ways: by producing novel combinations of familiar ideas; by exploring the potential of conceptual spaces; and by making transformations that enable the generation of previously impossible ideas. AI will have less difficulty in modelling the generation of new ideas than in automating their evaluation.},
language = {en},
number = {1},
urldate = {2021-11-26},
journal = {Artificial Intelligence},
author = {Boden, Margaret A.},
month = aug,
year = {1998},
pages = {347--356},
file = {Boden_1998_Creativity_and_artificial_intelligence.pdf:files/6957/Boden_1998_Creativity_and_artificial_intelligence.pdf:application/pdf},
}
@article{hieronymi_creativity_2013,
title = {Creativity from a systems perspective: {Bridging} theory and practice},
volume = {42},
shorttitle = {Creativity from a systems perspective},
doi = {10.1108/K-10-2012-0081},
abstract = {Purpose ‐ This paper aims to sketch the outline of a systems framework for creativity. It involves several levels of analysis and addresses researchers and practitioners. When improving creative climates in work settings, it is necessary to have a better understanding of the various mechanisms of creativity and what strengthens or diminishes them. Design/methodology/approach ‐ Creativity research is fragmented and involves multiple aspects, levels and disciplines, ranging from biology to psychology and sociology. Concepts from systems science have particular value in understanding creativity, as they provide a transdisciplinary language of how systems work and adapt. This conceptual paper makes use of the language and concepts from the systems field to connect often disparate perspectives and clarify key mechanisms of creativity. Findings ‐ The core of this paper is a newly developed multilevel model of the creative mind. The proposed concepts provide a starting point for integrating further theoretical findings. Practical implications ‐ Improved understanding of creativity could help leaders more effectively use their creativity while facilitating the creativity of others for successful cooperation and problem-solving. Originality/value ‐ The visual models introduced here help bridge theory and practice while creating a stronger link between creativity research and studies in systems, cybernetics and complexity.},
journal = {Kybernetes: The International Journal of Systems \& Cybernetics},
author = {Hieronymi, Andreas},
month = nov,
year = {2013},
file = {Hieronymi_2013_Creativity_from_a_systems_perspective.pdf:files/6959/Hieronymi_2013_Creativity_from_a_systems_perspective.pdf:application/pdf},
}
@book{paul_philosophy_2014,
address = {New York},
title = {The {Philosophy} of {Creativity}: {New} {Essays}},
isbn = {978-0-19-983696-3},
shorttitle = {The {Philosophy} of {Creativity}},
url = {https://oxford.universitypressscholarship.com/10.1093/acprof:oso/9780199836963.001.0001/acprof-9780199836963},
abstract = {Creativity pervades human life. It is the mark of individuality, the vehicle of self-expression, and the engine of progress in every human endeavor. It also raises a wealth of philosophical questions, but curiously, it hasn’t been a major topic in contemporary philosophy. The Philosophy of Creativity ventures to change that. Illustrating the value of interdisciplinary exchange, this is a series of new essays from some of today’s leading thinkers integrating philosophical insights with empirical research. Join them as they explore such issues as the role of consciousness in the creative process, the role of the audience in the creation of art, the emergence of creativity through childhood pretending, whether great works of literature give us insight into human nature, whether a computer program can really be creative, the definition of creativity, whether creativity is a virtue, the difference between creativity in science and art, and whether creativity can be taught—both in general and within philosophy itself.},
language = {eng},
urldate = {2021-11-29},
publisher = {Oxford University Press},
editor = {Paul, Elliot Samuel and Kaufman, Scott Barry},
year = {2014},
doi = {10.1093/acprof:oso/9780199836963.001.0001},
keywords = {consciousness, education, Artificial intelligence, creativity, cognitive science, imagination, innovation, insight, interdisciplinary, philosophy, philosophy of mind, virtue, Aesthetics},
}
@article{gaut_philosophy_2010,
title = {The {Philosophy} of {Creativity}},
volume = {5},
issn = {1747-9991},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1747-9991.2010.00351.x},
doi = {10.1111/j.1747-9991.2010.00351.x},
abstract = {This paper surveys some of the central issues in the philosophy of creativity and argues that an adequate treatment of them requires attention to the rich psychological literature on creativity. It also shows that the range of interesting philosophical questions to be raised about creativity is much wider than concerns its role in art. Issues covered include the definition of ‘creativity’; the relation of creativity to imagination; whether the creative process is rational; whether it is teleological; the relation of creativity to knowledge; whether creativity can be explained; computational and Darwinian theories of creativity; whether creativity is a virtue; the relation of creativity to tradition; the aesthetic value of creativity; and whether creative activity is different in science and art.},
language = {en},
number = {12},
urldate = {2021-11-29},
journal = {Philosophy Compass},
author = {Gaut, Berys},
year = {2010},
note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1747-9991.2010.00351.x},
pages = {1034--1046},
annote = {Commentaire Axel
Résumé
Historiquement, 2 noms :
-Platon ("inspiration is a kind of madness")
-Kant (creativity similar to imagination ; no creativity in sciences)
Peu de travaux avant les années 2000, et les ressources actuelles sont surtout en psychologie
Graham Wallace : 4 stages de processus créatifs (préparation, incubation, illumination, vérification)
Ward : generate and explore (2 stages)
Is creativity a virtue? plutôt oui pour la personalité créative, mais reliée à des vices ("hostile, impulsive"), faut-il désunir les qualificatifs?
Rationality of creativity : Association entre créativité, irrationalité et folie (see Platon), remis en question (ex Jon Elster : maximiser l'"artistic value" est un processus rationnel); correlation between psychopathologies and creativity
Créativité en opposition au traditionnel : besoin de traditions pour exprimer la créativité-{\textgreater} Créativité est culturelle
Modèle darwinien de la crativité : blind generation (DT?) into selection stage (CT?) Definir "blind" est important : pas full random, sinon on ne pourrait pas donner de crédit au processus créatif; bref, il faut essayer de bien définir blindness.
Can creativity be explained? Pas forcément possible d'en donner une explication naturaliste, mais on peut expliquer comment elle est possible (Briskman)
Boden : Combinational, exploratory, transformational. Discuté (par Novitz par ex) car les distinctions nécessitent un 'conceptual space" à explorer ou transformer, ce qui n'est pas forcément vrai. Searle : without understanding, no creativity.
Briskman : Dans tous les cas, la créativité est du problem-solving (peut-être différent pour les artiustes, d'où l'absence des découvertes indépendantes)
Def : original and valuable. Plutôt que original, la surprise peut être meilleure pour définir.
H-creativity (historical; no one else had the idea) \& P-creativity (psychological; new to individuals)
Dark creativity is valuable? No, destructiv-ity (Novitz); yes, because it serves the agent's purpose (Cropley)
Value and original alone? No,Tectonique des plaques -{\textgreater} prdouit des diamants et certaines structures sont originales.
Aussi, il faut exclure les résultats "par chance" (e.g renverser de la peinture)-{\textgreater} Nécessite du skill ou de la compréhension, du jugement individuel et une capacité d'évaluation de la tâche. Regroupé sous le terme de flair (flair)-{\textgreater} Novel, valuable by flair
CRéativity is not means-to-end (non téléologique) for eg Collingwood -{\textgreater} anti-teleological argument : bottom-up? propulsive model
rejection of anti-teleological argument : top-down? Connaître le goal, mais pas la démarche par exemple.
Imagination \& Créativité : l'un est une base de l'autre; pretend-play serait une base de créativité? Gaut indique que l'imagination peut être en état de créativité active, auquel cas cela rejoint la créativité.},
file = {Gaut_2010_The_Philosophy_of_Creativity.pdf:files/6985/Gaut_2010_The_Philosophy_of_Creativity.pdf:application/pdf;Snapshot:files/6986/j.1747-9991.2010.00351.html:text/html},
}
@misc{bordini_jason_2007,
title = {Jason – {A} {Java}-based interpreter for an extended version of {AgentSpeak}},
url = {http://jason.sourceforge.net/Jason.pdf},
language = {en},
author = {Bordini, Rafael H. and Hübner, Jomi F.},
year = {2007},
file = {Bordini_Hubner_2007_Jason_–_A_Java-based_interpreter_for_an_extended_version_of_AgentSpeak.pdf:files/7019/Bordini_Hubner_2007_Jason_–_A_Java-based_interpreter_for_an_extended_version_of_AgentSpeak.pdf:application/pdf;Citeseer - Snapshot:files/7018/summary.html:text/html},
}
@misc{bohler_dou_nodate,
title = {D’où vient la curiosité ?},
url = {https://www.cerveauetpsycho.fr/sd/neurosciences/d-ou-vient-la-curiosite-21975.php},
abstract = {La zona incerta est une zone du cerveau aux fonctions mystérieuses, qui suscite la curiosité. Or on vient de découvrir qu’une de ses fonctions est de donner naissance… au sentiment de curiosité.
Un article de vulgarisation basé sur M. Ahmadlou et al.,
A cell type–specific cortico-subcortical brain circuit for investigatory and novelty-seeking behavior, Science, vol. 372, p. 6543, 2021.},
language = {fr},
urldate = {2021-12-10},
journal = {cerveauetpsycho.fr},
author = {Bohler, Sébastien},
note = {Publisher: Pour la Science},
file = {Bohler_D’ou_vient_la_curiosite.pdf:files/6734/Bohler_D’ou_vient_la_curiosite.pdf:application/pdf;Snapshot:files/7020/d-ou-vient-la-curiosite-21975.html:text/html},
}
@book{allemang_semantic_2020,
address = {New York, NY, USA},
edition = {3},
title = {Semantic {Web} for the {Working} {Ontologist}: {Effective} {Modeling} for {Linked} {Data}, {RDFS}, and {OWL}},
isbn = {978-1-4503-7617-4},
shorttitle = {Semantic {Web} for the {Working} {Ontologist}},
url = {https://hal.inria.fr/hal-02939606},
abstract = {Enterprises have made amazing advances by taking advantage of data about their business to provide predictions and understanding of their customers, markets, and products. But as the world of business becomes more interconnected and global, enterprise data is no long a monolith; it is just a part of a vast web of data. Managing data on a world-wide scale is a key capability for any business today. The Semantic Web treats data as a distributed resource on the scale of the World Wide Web, and incorporates features to address the challenges of massive data distribution as part of its basic design. The aim of the first two editions was to motivate the Semantic Web technology stack from end-to-end; to describe not only what the Semantic Web standards are and how they work, but also what their goals are and why they were designed as they are. It tells a coherent story from beginning to end of how the standards work to manage a world-wide distributed web of knowledge in a meaningful way. The third edition builds on this foundation to bring Semantic Web practice to enterprise. Fabien Gandon joins Dean Allemang and Jim Hendler, bringing with him years of experience in global linked data, to open up the story to a modern view of global linked data. While the overall story is the same, the examples have been brought up to date and applied in a modern setting, where enterprise and global data come together as a living, linked network of data. Also included with the third edition, all of the data sets and queries are available online for study and experimentation at data.world/swwo.},
publisher = {Association for Computing Machinery},
author = {Allemang, Dean and Hendler, Jim and Gandon, Fabien},
year = {2020},
doi = {10.1145/3382097},
}
@article{cera_conceptions_2018,
title = {Conceptions of {Learning}, {Well}-being, and {Creativity} in {Older} {Adults}},
copyright = {Copyright (c) 2018 rosa cera, Carlo Cristini, Alessandro Antonietti},
issn = {2037-7924},
url = {https://www.ledonline.it/index.php/ECPS-Journal/article/view/1475},
doi = {10.7358/ecps-2018-018-cera},
abstract = {The goal of this study is to investigate the conceptions of learning shared by older adults and to assess the relationships of such conceptions with creativity and satisfaction with life. A sample of 322 older adults (mean age = 72 years) attending Universities of the Third Age were administered the shortened version of a questionnaire aimed at capturing opinions and feelings associated to learning, a task from the Torrance Tests of Creative Thinking, and the Satisfaction with Life Scale. Age, gender, schooling, occupation, marital status, and hobbies of the participants were taken into account. Factorial analyses showed that different conceptions of learning can be identified and that some of them are affected by age, gender, and the hobbies practised by the respondents. Older participants and women considered learning as an interpersonal and focused process to a larger extent. Older participants expressed negative feelings about learning, whereas women expressed positive feelings. Satisfaction with life changed according to marital status with married people scoring higher. Creative skills decreased with age and were influenced by gender, level of education, marital status, and hobbies practiced. Associations between conceptions of learning and satisfaction with life and creativity emerged. Implications for interventions addressing older adults’ well-being are discussed.},
language = {en},
number = {18},
urldate = {2021-12-10},
journal = {Journal of Educational, Cultural and Psychological Studies (ECPS Journal)},
author = {Cera, Rosa and Cristini, Carlo and Antonietti, Alessandro},
month = dec,
year = {2018},
note = {Number: 18},
keywords = {Creativity, Ageing, Conceptions of learning, Satisfaction with life, Well- being.},
pages = {241--273},
file = {Cera_et_al_2018_Conceptions_of_Learning,_Well-being,_and_Creativity_in_Older_Adults.pdf:files/7026/Cera_et_al_2018_Conceptions_of_Learning,_Well-being,_and_Creativity_in_Older_Adults.pdf:application/pdf},
}
@inproceedings{mercier_reinforcement_2021,
address = {Bratislava, Slovakia},
series = {Lecture {Notes} in {Computer} {Science}},
title = {Reinforcement {Symbolic} {Learning}},
isbn = {978-3-030-86380-7},
doi = {10.1007/978-3-030-86380-7_49},
abstract = {Complex problem solving involves representing structured knowledge, reasoning and learning, all at once. In this prospective study, we make explicit how a reinforcement learning paradigm can be applied to a symbolic representation of a concrete problem-solving task, modeled here by an ontology. This preliminary paper is only a set of ideas while feasibility verification is still a perspective of this work.},
language = {en},
booktitle = {Artificial {Neural} {Networks} and {Machine} {Learning} – {ICANN} 2021},
publisher = {Springer International Publishing},
author = {Mercier, Chloé and Alexandre, Frédéric and Viéville, Thierry},
editor = {Farkaš, Igor and Masulli, Paolo and Otte, Sebastian and Wermter, Stefan},
year = {2021},
keywords = {Models for learning sciences, Ontology edit distances, Reinforcement symbolic learning},
pages = {608--612},
file = {Mercier_et_al_2021_Reinforcement_Symbolic_Learning.pdf:files/7033/Mercier_et_al_2021_Reinforcement_Symbolic_Learning.pdf:application/pdf},
}
@incollection{tanaka_approach_2013,
address = {Dordrecht},
title = {An {Approach} to {Human}-{Level} {Commonsense} {Reasoning}},
isbn = {978-94-007-4437-0 978-94-007-4438-7},
url = {http://link.springer.com/10.1007/978-94-007-4438-7_12},
abstract = {Commonsense reasoning has proven exceedingly difficult both to model and to implement in artificial reasoning systems. This paper discusses some of the features of human reasoning that may account for this difficulty, surveys a number of reasoning systems and formalisms, and offers an outline of active logic, a non-classical paraconsistent logic that may be of some use in implementing commonsense reasoning.},
language = {en},
urldate = {2021-12-10},
booktitle = {Paraconsistency: {Logic} and {Applications}},
publisher = {Springer Netherlands},
author = {Anderson, Michael L. and Gomaa, Walid and Grant, John and Perlis, Don},
editor = {Tanaka, Koji and Berto, Francesco and Mares, Edwin and Paoli, Francesco},
year = {2013},
doi = {10.1007/978-94-007-4438-7_12},
pages = {201--222},
file = {Anderson_et_al_2013_An_Approach_to_Human-Level_Commonsense_Reasoning.pdf:files/7039/Anderson_et_al_2013_An_Approach_to_Human-Level_Commonsense_Reasoning.pdf:application/pdf;Snapshot:files/6926/An_Approach_to_Human_level_Commonsense_Reasoning.html:text/html},
}
@book{johnson_new_1994,
title = {The {New} {Circles} of {Learning}: {Cooperation} in the {Classroom} and {School}},
isbn = {978-0-87120-227-7},
shorttitle = {The {New} {Circles} of {Learning}},
abstract = {In this concise book, David and Roger Johnson and Edythe Johnson Holubec reinforce the cooperative learning theories found in Circles of Learning: Cooperation in the Classroom and expand those theories to include the school and school district. Offering a thorough description of cooperative learning and the research behind it, the authors explain how cooperative learning can be implemented in the classroom and why cooperation must pervade schooling at every level. They discuss not only formal cooperative learning but also informal cooperative learning, cooperative base groups, and cooperative structures. They emphasize that cooperation is more than a seating arrangement, that educators must attend to these essential components: * Positive interdependence * Individual accountability/personal responsibility * Face-to-face promotive interaction * Interpersonal and small-group skills * Group processing Conflict is inevitable in any environment, and the authors provide succinct advice on managing conflict to creative a cooperative environment, structuring academic controversies, teaching procedures and skills, structuring a peacemaking program, teaching negotiation/mediation procedures and skills, and arbitrating as a last resort. If you want a successful learning community where people support each other's efforts and treat one another with respect, helping students develop their cooperative learning skills should be a key part of your strategy--and with this book you can start doing that.},
language = {en},
publisher = {ASCD},
author = {Johnson, David W. and Johnson, Roger T. and Holubec, Edythe Johnson},
year = {1994},
note = {Google-Books-ID: jZVRDwAAQBAJ},
keywords = {Education / General, Education / Learning Styles},
}
@article{torrente_integration_2009,
title = {Integration and {Deployment} of {Educational} {Games} in e-{Learning} {Environments}: {The} {Learning} {Object} {Model} {Meets} {Educational} {Gaming}},
volume = {12},
issn = {1176-3647},
shorttitle = {Integration and {Deployment} of {Educational} {Games} in e-{Learning} {Environments}},
url = {https://www.jstor.org/stable/jeductechsoci.12.4.359},
abstract = {ABSTRACT Game-based learning is becoming popular in the academic discussion of Learning Technologies. However, even though the educational potential of games has been thoroughly discussed in the literature, the integration of the games into educational processes and how to efficiently deliver the games to the students are still open questions. This paper addresses the aspects of integration and automatic deployment of educational games in Learning Management Systems. This integration simplifies the introduction of games in educational settings, leveraging the pre-existing technological infrastructure. Our approach is based on the automatic packaging and exportation of games as self-contained Learning Objects that can be easily distributed through any LMS compliant with the current interoperability standards. We thus inherit the advantages of the Learning Object model in terms of interoperability and, when supported by the LMS, in terms of student tracking and assessment.},
language = {en},
number = {4},
urldate = {2021-12-15},
journal = {Journal of Educational Technology \& Society},
author = {Torrente, Javier and Moreno-Ger, Pablo and Martínez-Ortiz, Iván and Fernandez-Manjon, Baltasar},
year = {2009},
note = {Publisher: International Forum of Educational Technology \& Society},
pages = {359--371},
file = {Snapshot:files/7083/citations.html:text/html;Torrente_et_al_2009_Integration_and_Deployment_of_Educational_Games_in_e-Learning_Environments.pdf:files/7082/Torrente_et_al_2009_Integration_and_Deployment_of_Educational_Games_in_e-Learning_Environments.pdf:application/pdf},
}
@phdthesis{vallaeys_generaliser_2021,
type = {report},
title = {Généraliser les possibilités-nécessités pour l'apprentissage profond},
url = {https://hal.inria.fr/hal-03338721},
abstract = {Ce rapport porte sur un stage de 8 semaines effectué avec l’équipe Inria Mnemosyne travaillant sur l’action exploratoire AIDE (Artificial Intelligence Devoted to Education), et coencadré par Thierry Viéville et Chloé Mercier. Le cadre restait assez libre et peu défini, mais invitait à chercher à définir la notion de probabilité/nécessité étendue proposée, et tenter de l’appliquer à des exemples d’apprentissages.},
language = {fr},
urldate = {2021-12-15},
school = {Inria},
author = {Vallaeys, Théophane},
month = sep,
year = {2021},
note = {Pages: 1},
file = {Snapshot:files/6848/hal-03338721.html:text/html;Vallaeys_2021_Generaliser_les_possibilites-necessites_pour_l'apprentissage_profond.pdf:files/6849/Vallaeys_2021_Generaliser_les_possibilites-necessites_pour_l'apprentissage_profond.pdf:application/pdf},
}
@article{mekern_computational_2019,
series = {Creativity},
title = {Computational models of creativity: a review of single-process and multi-process recent approaches to demystify creative cognition},
volume = {27},
issn = {2352-1546},
shorttitle = {Computational models of creativity},
url = {https://www.sciencedirect.com/science/article/pii/S2352154618301256},
doi = {10.1016/j.cobeha.2018.09.008},
abstract = {Creativity is a compelling but heterogeneous phenomenon. As opposed to big-C creativity, which is regarded as limited to the rare brilliant mind, little-c creativity is indispensable in adaptive everyday behavior, serving to adjust to changing circumstances and challenges. Computational approaches help demystify human creativity by offering insights into the underlying mechanisms and their characteristics. Recently proposed computational models to creative cognition often focus on either divergent or convergent problem-solving, but some start to integrate these processes into broader cognitive frameworks. We briefly review the state-of-the-art in the field and point out theoretical overlap. We extract basic principles that most existing models agree on and desiderata on the way towards a comprehensive model.},
language = {en},
urldate = {2021-12-15},
journal = {Current Opinion in Behavioral Sciences},
author = {Mekern, Vera and Hommel, Bernhard and Sjoerds, Zsuzsika},
month = jun,
year = {2019},
pages = {47--54},
file = {Mekern_et_al_2019_Computational_models_of_creativity.pdf:files/7113/Mekern_et_al_2019_Computational_models_of_creativity.pdf:application/pdf},
}
@book{olteteanu_cognition_2020,
address = {Cham},
title = {Cognition and the {Creative} {Machine}: {Cognitive} {AI} for {Creative} {Problem} {Solving}},
isbn = {978-3-030-30321-1 978-3-030-30322-8},
shorttitle = {Cognition and the {Creative} {Machine}},
url = {http://link.springer.com/10.1007/978-3-030-30322-8},
language = {en},
urldate = {2021-12-16},
publisher = {Springer International Publishing},
author = {Oltețeanu, Ana-Maria},
year = {2020},
doi = {10.1007/978-3-030-30322-8},
file = {Olteteanu_2020_Cognition_and_the_Creative_Machine.pdf:files/7080/Olteteanu_2020_Cognition_and_the_Creative_Machine.pdf:application/pdf},
}
@incollection{gibson_theory_1977,
title = {The theory of affordances},
url = {https://hal.archives-ouvertes.fr/hal-00692033},
abstract = {James J Gibson introduced for the first time the word "affordances" in this 1977 paper.},
urldate = {2021-12-15},
booktitle = {Perceiving, acting, and knowing: toward an ecological psychology},
publisher = {Hillsdale, N.J. : Lawrence Erlbaum Associates},
author = {Gibson, James J.},
editor = {Robert E Shaw, John Bransford},
year = {1977},
keywords = {Affordance},
pages = {pp.67--82},
file = {Gibson_1977_The_theory_of_affordances.pdf:files/7066/Gibson_1977_The_theory_of_affordances.pdf:application/pdf;HAL Snapshot:files/7081/hal-00692033.html:text/html},
}
@incollection{asprino_ontology_2017,
series = {Studies on the {Semantic} {Web}},
title = {An {Ontology} {Design} {Pattern} for supporting behaviour arbitration in cognitive agents},
volume = {32},
abstract = {In this paper we present an Ontology Design Pattern for the definition of situation-driven behaviour selection and arbitration models for cognitive agents. The proposed pattern relies on the descriptions and situations ontology pattern, combined with a frame-based representation scheme. Inspired by the affordance theory and behaviour-based robotics principles, our reference model enables the definition of weighted relationships, or affordances, between situations (representing agent’s perception of the environmental and social context) and agent’s functional and behavioral abilities. These weighted links serve as a basis for supporting runtime task selection and arbitration policies, to dynamically and contextually select agent’s behaviour. The pattern is at the heart of the behaviour-based cognitive approach adopted in the EU H2020 MARIO project for the design of an autonomous service robot (i.e., the cognitive agent) to support elderly people with cognitive impairments.},
language = {en},
number = {Chapter 8},
booktitle = {Advances in {Ontology} {Design} and {Patterns}},
author = {Asprino, Luigi and Nuzzolese, Andrea Giovanni and Russo, Alessandro and Gangemi, Aldo and Presutti, Valentina and Nolfi, Stefano},
year = {2017},
pages = {10},
file = {Asprino et al. - An Ontology Design Pattern for supporting behaviou.pdf:files/7238/Asprino et al. - An Ontology Design Pattern for supporting behaviou.pdf:application/pdf},
}
@misc{smith_basic_2015,
title = {Basic {Formal} {Ontology} 2.0},
author = {Smith, Barry},
year = {2015},
file = {Basic_Formal_Ontology_2.pdf:files/7084/Basic_Formal_Ontology_2.pdf:application/pdf},
}
@inproceedings{fuchs_cognitive_2018,
address = {Stuttgart},
title = {Cognitive {Space} {Time}: {A} {Model} for {Human}-{Centered} {Adaptivity} in {E}-{Learning}},
isbn = {978-1-5386-1469-3},
shorttitle = {Cognitive {Space} {Time}},
url = {https://ieeexplore.ieee.org/document/8436283/},
doi = {10.1109/ICE.2018.8436283},
abstract = {We introduce a model for the implementation of human-centered adaptive systems in the field of e-learning. We use ontologies to create a machine-processable representation of learners, learning content and their semantics. We also introduce the concept of “Cognitive Space Time”, abbreviated as CST. This is a multi-dimensional hyperspace the dimensions of which represent arbitrary meta data items describing the properties and semantics of learning material as well as personal traits and the progress of a learner. Recorded over time, each learner draws a trajectory in that hyperspace, which we build and analyze with spatio-temporal data structures and algorithms that are known from the field of spatio-temporal databases. Finally, we explain how our ontologies and the CST can be used to create adaptive systems. We do this on a universal basis that is derived from the concept of the Turing machine. Therefore, our idea provides a technology-independent design strategy that can be implemented in any form of automaton. Both the ontology approach and the CST have been implemented in prototype systems that are presented in this document.},
language = {en},
urldate = {2021-12-15},
booktitle = {2018 {IEEE} {International} {Conference} on {Engineering}, {Technology} and {Innovation} ({ICE}/{ITMC})},
publisher = {IEEE},
author = {Fuchs, Kevin and Henning, Peter A.},
month = jun,
year = {2018},
pages = {1--9},
file = {Fuchs_Henning_2018_Cognitive_Space_Time.pdf:files/7085/Fuchs_Henning_2018_Cognitive_Space_Time.pdf:application/pdf},
}
@article{turner_cognitive_2012,
title = {The cognitive paradigm ontology: design and application},
volume = {10},
issn = {1559-0089},
shorttitle = {The cognitive paradigm ontology},
doi = {10.1007/s12021-011-9126-x},
abstract = {We present the basic structure of the Cognitive Paradigm Ontology (CogPO) for human behavioral experiments. While the experimental psychology and cognitive neuroscience literature may refer to certain behavioral tasks by name (e.g., the Stroop paradigm or the Sternberg paradigm) or by function (a working memory task, a visual attention task), these paradigms can vary tremendously in the stimuli that are presented to the subject, the response expected from the subject, and the instructions given to the subject. Drawing from the taxonomy developed and used by the BrainMap project ( www.brainmap.org ) for almost two decades to describe key components of published functional imaging results, we have developed an ontology capable of representing certain characteristics of the cognitive paradigms used in the fMRI and PET literature. The Cognitive Paradigm Ontology is being developed to be compliant with the Basic Formal Ontology (BFO), and to harmonize where possible with larger ontologies such as RadLex, NeuroLex, or the Ontology of Biomedical Investigations (OBI). The key components of CogPO include the representation of experimental conditions focused on the stimuli presented, the instructions given, and the responses requested. The use of alternate and even competitive terminologies can often impede scientific discoveries. Categorization of paradigms according to stimulus, response, and instruction has been shown to allow advanced data retrieval techniques by searching for similarities and contrasts across multiple paradigm levels. The goal of CogPO is to develop, evaluate, and distribute a domain ontology of cognitive paradigms for application and use in the functional neuroimaging community.},
language = {eng},
number = {1},
journal = {Neuroinformatics},
author = {Turner, Jessica A. and Laird, Angela R.},
month = jan,
year = {2012},
pmid = {21643732},
pmcid = {PMC3682219},
keywords = {Humans, Cognition, Brain Mapping, Magnetic Resonance Imaging, Biomedical Research, Positron-Emission Tomography, Terminology as Topic},
pages = {57--66},
file = {Turner_Laird_2012_The_cognitive_paradigm_ontology.pdf:files/7086/Turner_Laird_2012_The_cognitive_paradigm_ontology.pdf:application/pdf},
}
@article{perisic_semantic_2018,
title = {A semantic approach to enhance moodle with personalization},
doi = {10.1002/cae.21929},
abstract = {A framework for an adaptive mechanism implemented in Moodle in order to improve learning outcomes and students' satisfaction with the learning process and student's feedback from regarding its usefulness was positive. The purpose of this paper is to present a framework for an adaptive mechanism implemented in Moodle in order to improve learning outcomes and students' satisfaction with the learning process. The proposed mechanism adapts the learning content within the course according to students' characteristics expressed by their learning style. In our study, student's learning style is dynamically determined by monitoring students’ actions and activities during the learning process, and detecting patterns of behavior that correspond to specific learning style. Semantic web technologies are in the background of the entire adaptive system. In order to examine the effectiveness of the proposed model and students' feedback, an evaluation study was conducted on two groups of students. Students from the control group had access to standard Moodle course, while students from experimental group had access to personalized learning content. The results indicated that students' performance was improved by using the proposed framework, while the student's feedback from regarding its usefulness was positive.},
journal = {Comput. Appl. Eng. Educ.},
author = {Perisic, Jasmina and Milovanovic, M. and Kazi, Z.},
year = {2018},
file = {Perisic_et_al_2018_A_semantic_approach_to_enhance_moodle_with_personalization.pdf:files/7088/Perisic_et_al_2018_A_semantic_approach_to_enhance_moodle_with_personalization.pdf:application/pdf},
}
@incollection{aime_chapitre_2021,
edition = {Éditions Matériologiques},
series = {Modélisations, simulations, systèmes complexes},
title = {Chapitre 2. {Apport} de l’ingénierie ontologique à la psychologie cognitive},
isbn = {978-2-37361-260-8},
url = {https://www.cairn.info/modelisation-ontologique-et-psychologies--9782373612608-page-95.htm},
language = {fr},
urldate = {2021-12-13},
booktitle = {Modélisation ontologique \& psychologies. {Une} influence réciproque},
publisher = {Éditions Matériologiques},
author = {Aimé, Xavier and Arnould, Frank},
month = may,
year = {2021},
note = {Bibliographie\_available: 0
Cairndomain: www.cairn.info
Cite Par\_available: 0},
pages = {95--160},
file = {Aime_Arnould_2021_Chapitre_2.pdf:files/7091/Aime_Arnould_2021_Chapitre_2.pdf:application/pdf;Snapshot:files/7094/modelisation-ontologique-et-psychologies--9782373612608-page-95.html:text/html},
}
@article{poldrack_cognitive_2011,
title = {The {Cognitive} {Atlas}: {Toward} a {Knowledge} {Foundation} for {Cognitive} {Neuroscience}},
volume = {5},
shorttitle = {The {Cognitive} {Atlas}},
doi = {10.3389/fninf.2011.00017},
abstract = {Cognitive neuroscience aims to map mental processes onto brain function, which begs the question of what "mental processes" exist and how they relate to the tasks that are used to manipulate and measure them. This topic has been addressed informally in prior work, but we propose that cumulative progress in cognitive neuroscience requires a more systematic approach to representing the mental entities that are being mapped to brain function and the tasks used to manipulate and measure mental processes. We describe a new open collaborative project that aims to provide a knowledge base for cognitive neuroscience, called the Cognitive Atlas (accessible online at http://www.cognitiveatlas.org), and outline how this project has the potential to drive novel discoveries about both mind and brain.},
journal = {Frontiers in neuroinformatics},
author = {Poldrack, Russell and Kittur, Aniket and Kalar, Donald and Seppa, Christian and Gil, Yolanda and Parker, D and Sabb, Fred and Bilder, Robert},
month = sep,
year = {2011},
pages = {17},
file = {Poldrack_et_al_2011_The_Cognitive_Atlas.pdf:files/7095/Poldrack_et_al_2011_The_Cognitive_Atlas.pdf:application/pdf},
}
@incollection{guarino_overview_2009,
title = {An {Overview} of {OntoClean}},
abstract = {OntoClean is a methodology for validating the ontological adequacy and logical consistency of taxonomic relationships. It
is based on highly general ontological notions drawn from philosophy, like essence, identity, and unity, which are used to elicit and characterize the intended meaning of properties, classes, and relations making up an ontology.
These aspects are represented by formal metaproperties, which impose several constraints on the taxonomic relationships between
concepts. The analysis of these constraints helps in evaluating and validating the choices made. In this chapter we present
an informal overview of the philosophical notions involved and their role in OntoClean, review some common ontological pitfalls,
and walk through the example that has appeared in pieces in previous papers and has been the basis of numerous tutorials and
talks.},
author = {Guarino, Nicola and Welty, Christopher},
month = may,
year = {2009},
doi = {10.1007/978-3-540-92673-3_9},
pages = {201--220},
file = {Guarino_Welty_2009_An_Overview_of_OntoClean.pdf:files/7097/Guarino_Welty_2009_An_Overview_of_OntoClean.pdf:application/pdf},
}
@article{guarino_evaluating_2002,
title = {Evaluating ontological decisions with ontoclean},
volume = {45},
journal = {Communications of the ACM},
author = {Guarino, Nicola and Welty, Christopher},
month = feb,
year = {2002},
pages = {61--65},
file = {Guarino_Welty_2002_Evaluating_ontological_decisions_with_ontoclean.pdf:files/7099/Guarino_Welty_2002_Evaluating_ontological_decisions_with_ontoclean.pdf:application/pdf},
}
@article{denervaud_education_2021,
title = {Education shapes the structure of semantic memory and impacts creative thinking},
volume = {6},
copyright = {2021 The Author(s)},
issn = {2056-7936},
url = {https://www.nature.com/articles/s41539-021-00113-8},
doi = {10.1038/s41539-021-00113-8},
abstract = {Education is central to the acquisition of knowledge, such as when children learn new concepts. It is unknown, however, whether educational differences impact not only what concepts children learn, but how those concepts come to be represented in semantic memory—a system that supports higher cognitive functions, such as creative thinking. Here we leverage computational network science tools to study hidden knowledge structures of 67 Swiss schoolchildren from two distinct educational backgrounds—Montessori and traditional, matched on socioeconomic factors and nonverbal intelligence—to examine how educational experience shape semantic memory and creative thinking. We find that children experiencing Montessori education show a more flexible semantic network structure (high connectivity/short paths between concepts, less modularity) alongside higher scores on creative thinking tests. The findings indicate that education impacts how children represent concepts in semantic memory and suggest that different educational experiences can affect higher cognitive functions, including creative thinking.},
language = {en},
number = {1},
urldate = {2021-12-13},
journal = {npj Science of Learning},
author = {Denervaud, Solange and Christensen, Alexander P. and Kenett, Yoed N. and Beaty, Roger E.},
month = dec,
year = {2021},
note = {Bandiera\_abtest: a
Cc\_license\_type: cc\_by
Cg\_type: Nature Research Journals
Number: 1
Primary\_atype: Research
Publisher: Nature Publishing Group
Subject\_term: Human behaviour;Long-term memory
Subject\_term\_id: human-behaviour;long-term-memory},
keywords = {Human behaviour, Long-term memory},
pages = {1--7},
file = {Denervaud_et_al_2021_Education_shapes_the_structure_of_semantic_memory_and_impacts_creative_thinking.pdf:files/7102/Denervaud_et_al_2021_Education_shapes_the_structure_of_semantic_memory_and_impacts_creative_thinking.pdf:application/pdf;Snapshot:files/7101/s41539-021-00113-8.html:text/html},
}
@article{kajic_spiking_2017,
title = {A {Spiking} {Neuron} {Model} of {Word} {Associations} for the {Remote} {Associates} {Test}},
volume = {8},
issn = {1664-1078},
url = {https://www.frontiersin.org/article/10.3389/fpsyg.2017.00099},
doi = {10.3389/fpsyg.2017.00099},
abstract = {Generating associations is important for cognitive tasks including language acquisition and creative problem solving. It remains an open question how the brain represents and processes associations. The Remote Associates Test (RAT) is a task, originally used in creativity research, that is heavily dependent on generating associations in a search for the solutions to individual RAT problems. In this work we present a model that solves the test. Compared to earlier modeling work on the RAT, our hybrid (i.e., non-developmental) model is implemented in a spiking neural network by means of the Neural Engineering Framework (NEF), demonstrating that it is possible for spiking neurons to be organized to store the employed representations and to manipulate them. In particular, the model shows that distributed representations can support sophisticated linguistic processing. The model was validated on human behavioral data including the typical length of response sequences and similarity relationships in produced responses. These data suggest two cognitive processes that are involved in solving the RAT: one process generates potential responses and a second process filters the responses.},
urldate = {2021-12-18},
journal = {Frontiers in Psychology},
author = {Kajić, Ivana and Gosmann, Jan and Stewart, Terrence C. and Wennekers, Thomas and Eliasmith, Chris},
year = {2017},
pages = {99},
file = {Kajić et al_2017_A Spiking Neuron Model of Word Associations for the Remote Associates Test.pdf:files/7116/Kajić et al_2017_A Spiking Neuron Model of Word Associations for the Remote Associates Test.pdf:application/pdf},
}
@article{augello_artwork_2015,
title = {Artwork creation by a cognitive architecture integrating computational creativity and dual process approaches},
volume = {15},
url = {http://arxiv.org/abs/1601.00669},
doi = {10.1016/j.bica.2015.09.007},
abstract = {The paper proposes a novel cognitive architecture (CA) for computational creativity based on the Psi model and on the mechanisms inspired by dual process theories of reasoning and rationality. In recent years, many cognitive models have focused on dual process theories to better describe and implement complex cognitive skills in artificial agents, but creativity has been approached only at a descriptive level. In previous works we have described various modules of the cognitive architecture that allows a robot to execute creative paintings. By means of dual process theories we refine some relevant mechanisms to obtain artworks, and in particular we explain details about resolution level of the CA dealing with different strategies of access to the Long Term Memory (LTM) and managing the interaction between S1 and S2 processes of the dual process theory. The creative process involves both divergent and convergent processes in either implicit or explicit manner. This leads to four activities (exploratory, reflective, tacit, and analytic) that, triggered by urges and motivations, generate creative acts. These creative acts exploit both the LTM and the WM in order to make novel substitutions to a perceived image by properly mixing parts of pictures coming from different domains. The paper highlights the role of the interaction between S1 and S2 processes, modulated by the resolution level which focuses the attention of the creative agent by broadening or narrowing the exploration of novel solutions, or even drawing the solution from a set of already made associations. An example of artificial painter is described in some experimentations by using a robotic platform.},
journal = {Biologically Inspired Cognitive Architectures},
author = {Augello, Agnese and Infantino, Ignazio and Lieto, Antonio and Pilato, Giovanni and Rizzo, Riccardo and Vella, Filippo},
month = oct,
year = {2015},
keywords = {Computer Science - Artificial Intelligence},
annote = {Comment: 30 pages, 8 figures, to appear in Biologically Inspired Cognitive Architectures 2016},
file = {arXiv.org Snapshot:files/7134/1601.html:text/html;Augello_et_al_2015_Artwork_creation_by_a_cognitive_architecture_integrating_computational.pdf:files/7225/Augello_et_al_2015_Artwork_creation_by_a_cognitive_architecture_integrating_computational.pdf:application/pdf},
}
@article{augello_introducing_2013,
series = {{BICA} 2013: {Papers} from the {Fourth} {Annual} {Meeting} of the {BICA} {Society}},
title = {Introducing a creative process on a cognitive architecture},
volume = {6},
issn = {2212-683X},
url = {https://www.sciencedirect.com/science/article/pii/S2212683X13000467},
doi = {10.1016/j.bica.2013.05.011},
abstract = {In this paper we present a system that implements a creative behavior on a cognitive architecture. It is aimed at creating digital art images from snapshots of a human subject, simulating a simple creative process. Such a process starts from a Training Phase that creates a set of image filter sequences. This phase is oriented to approximate some painting styles obtained from famous images and portraits of the past. The learned filter sequences are then used during the Production Phase. During this subsequent phase, the “artificial artist” interacts with the subject trying to “catch” the human emotions that drive the creation of the portrait. The artist processes feedbacks from the user according to the cognitive model Psi and its implementation of the motivations. These motivations influence further modifications of the applied filter sequences achieving an evolution of the artificial artist.},
language = {en},
urldate = {2021-12-21},
journal = {Biologically Inspired Cognitive Architectures},
author = {Augello, Agnese and Infantino, Ignazio and Pilato, Giovanni and Rizzo, Riccardo and Vella, Filippo},
month = oct,
year = {2013},
keywords = {Computer graphics, Picture/image generation},
pages = {131--139},
file = {Augello_et_al_2013_Introducing_a_creative_process_on_a_cognitive_architecture.pdf:files/7136/Augello_et_al_2013_Introducing_a_creative_process_on_a_cognitive_architecture.pdf:application/pdf},
}
@book{boden_creative_2004,
title = {The {Creative} {Mind}: {Myths} and {Mechanisms}},
isbn = {978-0-415-31452-7},
shorttitle = {The {Creative} {Mind}},
abstract = {How is it possible to think new thoughts? What is creativity and can science explain it? And just how did Coleridge dream up the creatures of The Ancient Mariner? When The Creative Mind: Myths and Mechanisms was first published, Margaret A. Boden's bold and provocative exploration of creativity broke new ground. Boden uses examples such as jazz improvisation, chess, story writing, physics, and the music of Mozart, together with computing models from the field of artificial intelligence to uncover the nature of human creativity in the arts. The second edition of The Creative Mind has been updated to include recent developments in artificial intelligence, with a new preface, introduction and conclusion by the author. It is an essential work for anyone interested in the creativity of the human mind.},
language = {en},
publisher = {Psychology Press},
author = {Boden, Margaret A.},
year = {2004},
note = {Google-Books-ID: 6Zkm4dz32Y4C},
keywords = {Philosophy / General},
}
@article{zhang_approaching_2016,
title = {Approaching the {Distinction} between {Intuition} and {Insight}},
volume = {7},
issn = {1664-1078},
url = {https://www.frontiersin.org/article/10.3389/fpsyg.2016.01195},
doi = {10.3389/fpsyg.2016.01195},
abstract = {Intuition and insight share similar cognitive and neural basis. Though, there are still some essential differences between the two. Here in this short review, we discriminated between intuition, and insight in two aspects. First, intuition, and insight are toward different aspects of information processing. Whereas intuition involves judgment about “yes or no,” insight is related to “what” is the solution. Second, tacit knowledge play different roles in between intuition and insight. On the one hand, tacit knowledge is conducive to intuitive judgment. On the other hand, tacit knowledge may first impede but later facilitate insight occurrence. Furthermore, we share theoretical, and methodological views on how to access the distinction between intuition and insight.},
urldate = {2021-12-21},
journal = {Frontiers in Psychology},
author = {Zhang, Zhonglu and Lei, Yi and Li, Hong},
year = {2016},
pages = {1195},
file = {Zhang et al_2016_Approaching the Distinction between Intuition and Insight.pdf:files/7140/Zhang et al_2016_Approaching the Distinction between Intuition and Insight.pdf:application/pdf},
}
@article{oreilly_what_2010,
title = {The {What} and {How} of {Prefrontal} {Cortical} {Organization}},
volume = {33},
issn = {0166-2236},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2916029/},
doi = {10.1016/j.tins.2010.05.002},
abstract = {How is the prefrontal cortex (PFC) organized such that it is capable of making people more flexible and in control of their behavior? Is there any systematic organization across the many diverse areas that comprise the PFC, or is it uniquely adaptive such that no fixed representation structure can develop? Going against the current tide, this paper argues that there is indeed a systematic organization across PFC areas, with an important functional distinction between ventral and dorsal regions characterized as processing What vs. How information, respectively. This distinction has implications for the rostro-caudal and medial-lateral axes of organization as well. The resulting large-scale functional map of PFC may prove useful in integrating diverse data, and generating novel predictions.},
number = {8},
urldate = {2021-12-21},
journal = {Trends in neurosciences},
author = {O’Reilly, Randall C.},
month = aug,
year = {2010},
pmid = {20573407},
pmcid = {PMC2916029},
pages = {355--361},
file = {O’Reilly_2010_The What and How of Prefrontal Cortical Organization.pdf:files/7143/O’Reilly_2010_The What and How of Prefrontal Cortical Organization.pdf:application/pdf},
}
@article{friston_learning_2003,
title = {Learning and inference in the brain},
volume = {16},
issn = {0893-6080},
doi = {10.1016/j.neunet.2003.06.005},
abstract = {This article is about how the brain data mines its sensory inputs. There are several architectural principles of functional brain anatomy that have emerged from careful anatomic and physiologic studies over the past century. These principles are considered in the light of representational learning to see if they could have been predicted a priori on the basis of purely theoretical considerations. We first review the organisation of hierarchical sensory cortices, paying special attention to the distinction between forward and backward connections. We then review various approaches to representational learning as special cases of generative models, starting with supervised learning and ending with learning based upon empirical Bayes. The latter predicts many features, such as a hierarchical cortical system, prevalent top-down backward influences and functional asymmetries between forward and backward connections that are seen in the real brain. The key points made in article are: (i). hierarchical generative models enable the learning of empirical priors and eschew prior assumptions about the causes of sensory input that are inherent in non-hierarchical models. These assumptions are necessary for learning schemes based on information theory and efficient or sparse coding, but are not necessary in a hierarchical context. Critically, the anatomical infrastructure that may implement generative models in the brain is hierarchical. Furthermore, learning based on empirical Bayes can proceed in a biologically plausible way. (ii). The second point is that backward connections are essential if the processes generating inputs cannot be inverted, or the inversion cannot be parameterised. Because these processes involve many-to-one mappings, are non-linear and dynamic in nature, they are generally non-invertible. This enforces an explicit parameterisation of generative models (i.e. backward connections) to afford recognition and suggests that forward architectures, on their own, are not sufficient for perception. (iii). Finally, non-linearities in generative models, mediated by backward connections, require these connections to be modulatory, so that representations in higher cortical levels can interact to predict responses in lower levels. This is important in relation to functional asymmetries in forward and backward connections that have been demonstrated empirically.},
language = {eng},
number = {9},
journal = {Neural Networks: The Official Journal of the International Neural Network Society},
author = {Friston, Karl},
month = nov,
year = {2003},
pmid = {14622888},
keywords = {Learning, Neural Networks, Computer, Brain, Bayes Theorem},
pages = {1325--1352},
file = {Friston_2003_Learning_and_inference_in_the_brain.pdf:files/7146/Friston_2003_Learning_and_inference_in_the_brain.pdf:application/pdf},
}
@article{corbetta_control_2002,
title = {Control of goal-directed and stimulus-driven attention in the brain},
volume = {3},
copyright = {2002 Nature Publishing Group},
issn = {1471-0048},
url = {https://www.nature.com/articles/nrn755},
doi = {10.1038/nrn755},
abstract = {This review proposes that two networks of brain areas are involved in controlling attention. One network is primarily responsible for applying cognitive, top-down selection for stimuli and responses, whereas the other detects behaviourally relevant stimuli and might act as a 'circuit breaker' for the first system. Humans use cognitive information to direct attention to relevant objects (targets) in a visual scene. Information such as the target's colour or location is represented as a 'perceptual set'. Similarly, advance information about the required response to a target is represented as a 'motor set'. These can be considered together as an 'attentional set', which aids the detection of and response to targets. Such top-down control of attentional processes activates dorsal posterior parietal and frontal regions of the brain bilaterally in both monkeys and humans. This dorsal frontoparietal system is responsible for the generation of attentional sets. Attention can also be driven by stimulus properties rather than cognitive processes. This 'bottom-up' control of attention explains why we find ourselves drawn to 'oddball' stimuli that are very different from the background, or to salient stimuli that share some sensory features, such as colour, with the target for which we are searching. The dorsal frontoparietal system seems to maintain a 'salience map' that combines bottom-up with top-down information during visual search. Potentially important sensory stimuli, such as loud alarms or sudden movement, can attract our attention regardless of the ongoing task. This sensory orienting process seems to be mediated by the second attentional network, which is mainly lateralized to the right side of the brain and includes the temporoparietal junction and the ventral frontal cortex. This network seems to interrupt ongoing cognitive activity when a stimulus that might be behaviourally important is detected. These two networks could interact in humans to control attention. It is possible that damage to these networks is responsible for the syndrome of neglect, in which patients that have suffered damage to the right side of the brain tend to ignore stimuli on the left side of space. The authors suggest that neglect results from damage to the ventral network that also 'functionally inactivates' the dorsal network.},
language = {en},
number = {3},
urldate = {2021-12-22},
journal = {Nature Reviews Neuroscience},
author = {Corbetta, Maurizio and Shulman, Gordon L.},
month = mar,
year = {2002},
note = {Bandiera\_abtest: a
Cg\_type: Nature Research Journals
Number: 3
Primary\_atype: Reviews
Publisher: Nature Publishing Group},
keywords = {Neurobiology, Neurosciences, Animal Genetics and Genomics, Behavioral Sciences, Biological Techniques, Biomedicine, general},
pages = {201--215},
file = {Corbetta_Shulman_2002_Control_of_goal-directed_and_stimulus-driven_attention_in_the_brain.pdf:files/7150/Corbetta_Shulman_2002_Control_of_goal-directed_and_stimulus-driven_attention_in_the_brain.pdf:application/pdf;Snapshot:files/7151/nrn755.html:text/html},
}
@article{ede_goal-directed_2020,
title = {Goal-directed and stimulus-driven selection of internal representations},
volume = {117},
copyright = {Copyright © 2020 the Author(s). Published by PNAS.. https://creativecommons.org/licenses/by/4.0/This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY).},
issn = {0027-8424, 1091-6490},
url = {https://www.pnas.org/content/117/39/24590},
doi = {10.1073/pnas.2013432117},
abstract = {Adaptive behavior relies on the selection of relevant sensory information from both the external environment and internal memory representations. In understanding external selection, a classic distinction is made between voluntary (goal-directed) and involuntary (stimulus-driven) guidance of attention. We have developed a task—the anti-retrocue task—to separate and examine voluntary and involuntary guidance of attention to internal representations in visual working memory. We show that both voluntary and involuntary factors influence memory performance but do so in distinct ways. Moreover, by tracking gaze biases linked to attentional focusing in memory, we provide direct evidence for an involuntary “retro-capture” effect whereby external stimuli involuntarily trigger the selection of feature-matching internal representations. We show that stimulus-driven and goal-directed influences compete for selection in memory, and that the balance of this competition—as reflected in oculomotor signatures of internal attention—predicts the quality of ensuing memory-guided behavior. Thus, goal-directed and stimulus-driven factors together determine the fate not only of perception, but also of internal representations in working memory.},
language = {en},
number = {39},
urldate = {2021-12-22},
journal = {Proceedings of the National Academy of Sciences},
author = {Ede, Freek van and Board, Alexander G. and Nobre, Anna C.},
month = sep,
year = {2020},
pmid = {32929036},
note = {Publisher: National Academy of Sciences
Section: Biological Sciences},
keywords = {attention, capture, memory-guided behavior, oculomotor system, visual working memory},
pages = {24590--24598},
file = {Ede_et_al_2020_Goal-directed_and_stimulus-driven_selection_of_internal_representations.pdf:files/7153/Ede_et_al_2020_Goal-directed_and_stimulus-driven_selection_of_internal_representations.pdf:application/pdf;Snapshot:files/7155/24590.html:text/html},
}
@inproceedings{chateau-laurent_towards_2021,
title = {Towards a {Computational} {Cognitive} {Neuroscience} {Model} of {Creativity}},
url = {https://hal.inria.fr/hal-03359407},
abstract = {Recent progress in AI has expanded the boundaries of the cognitive functions that can be simulated, but creativity remains a challenge. Neuroscience sheds light on its mechanisms and its tight relationship with episodic memory and cognitive control, while machine learning provides preliminary models of these mechanisms. We present these lines of research and explain how they can be exploited in the domain of computational creativity in order to further expand the capabilities of AI.},
language = {en},
urldate = {2021-12-22},
booktitle = {{IEEE} {ICCI}*{CC}'21 - 20th {IEEE} {International} {Conference} on {Cognitive} {Informatics} and {Cognitive} {Computing}},
author = {Chateau-Laurent, Hugo and Alexandre, Frédéric},
month = oct,
year = {2021},
file = {Chateau-Laurent_Alexandre_2021_Towards a Computational Cognitive Neuroscience Model of Creativity.pdf:files/7159/Chateau-Laurent_Alexandre_2021_Towards a Computational Cognitive Neuroscience Model of Creativity.pdf:application/pdf;Snapshot:files/7160/hal-03359407.html:text/html},
}
@article{stachenfeld_hippocampus_2017,
title = {The hippocampus as a predictive map},
volume = {20},
copyright = {2017 Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.},
issn = {1546-1726},
url = {https://www.nature.com/articles/nn.4650},
doi = {10.1038/nn.4650},
abstract = {The authors show how predictive representations are useful for maximizing future reward, particularly in spatial domains. They develop a predictive-map model of hippocampal place cells and entorhinal grid cells that captures a wide variety of effects from human and rodent literature.},
language = {en},
number = {11},
urldate = {2021-12-23},
journal = {Nature Neuroscience},
author = {Stachenfeld, Kimberly L. and Botvinick, Matthew M. and Gershman, Samuel J.},
month = nov,
year = {2017},
note = {Bandiera\_abtest: a
Cg\_type: Nature Research Journals
Number: 11
Primary\_atype: Research
Publisher: Nature Publishing Group
Subject\_term: Hippocampus;Learning and memory;Reward
Subject\_term\_id: hippocampus;learning-and-memory;reward},
keywords = {Hippocampus, Reward, Learning and memory},
pages = {1643--1653},
file = {Snapshot:files/7162/nn.html:text/html;Stachenfeld et al_2017_The hippocampus as a predictive map.pdf:files/7163/Stachenfeld et al_2017_The hippocampus as a predictive map.pdf:application/pdf},
}
@article{raufaste_testing_2003,
series = {Fuzzy {Set} and {Possibility} {Theory}-{Based} {Methods} in {Artificial} {Intelligence}},
title = {Testing the descriptive validity of possibility theory in human judgments of uncertainty},
volume = {148},
issn = {0004-3702},
url = {https://www.sciencedirect.com/science/article/pii/S0004370203000213},
doi = {10.1016/S0004-3702(03)00021-3},
abstract = {Many works in the past showed that human judgments of uncertainty do not conform very well to probability theory. The present paper reports four experiments that were conducted in order to evaluate if human judgments of uncertainty conform better to possibility theory. At first, two experiments investigate the descriptive properties of some basic possibilistic measures. Then a new measurement apparatus is used, the Ψ-scale, to compare possibilistic vs. probabilistic disjunction and conjunction. Results strongly suggest that a human judgment is qualitative in essence, closer to a possibilistic than to a probabilistic approach of uncertainly. The paper also describes a qualitative heuristic, for conjunction, which was used by expert radiologists.},
language = {en},
number = {1},
urldate = {2021-12-27},
journal = {Artificial Intelligence},
author = {Raufaste, Eric and da Silva Neves, Rui and Mariné, Claudette},
month = aug,
year = {2003},
keywords = {Diagnosis, Possibility theory, Uncertainty, Decision-making, Judgment},
pages = {197--218},
}
@article{smithson_human_1970,
title = {Human {Judgment} {And} {Imprecise} {Probabilities}},
abstract = {Introduction The study of human judgment under uncertainty has a history that is almost contemporaneous with that of probability theories. This is not a coincidence. From the outset, the idea of using probability to describe cognitive states or aspects of subjective judgment has provoked debate, theory construction, and empirical research. It is no exaggeration to say that probability theories have exerted a strong prescriptive influence on the study of judgment and decision making (see Gigerenzer 1994 [21] and Smithson 1989 [41] for overviews). In the modern era, proponents of the Subjective Expected Utility (SEU) framework advocated a version of Bayesianism as the benchmark for rational judgment and decision making, and this viewpoint dominated studies of human judgment and decision making during the 50's and 60's. By the late 70's and early 80's, some scholars had begun to question whether we should regard deviations from probability theories as "irrational" (cf. Cohen 198},
author = {Smithson, Michael},
month = feb,
year = {1970},
file = {Smithson_1970_Human_Judgment_And_Imprecise_Probabilities.pdf:files/7166/Smithson_1970_Human_Judgment_And_Imprecise_Probabilities.pdf:application/pdf},
}
@article{mccay-peet_investigating_2015,
title = {Investigating serendipity: {How} it unfolds and what may influence it},
volume = {66},
issn = {2330-1643},
shorttitle = {Investigating serendipity},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/asi.23273},
doi = {10.1002/asi.23273},
abstract = {Serendipity is not an easy word to define. Its meaning has been stretched to apply to experiences ranging from the mundane to the exceptional. Serendipity, however, is consistently associated with unexpected and positive personal, scholarly, scientific, organizational, and societal events and discoveries. Diverse serendipitous experiences share a conceptual space; therefore, what lessons can we draw from an exploration of how serendipity unfolds and what may influence it? This article describes an investigation of work-related serendipity. Twelve professionals and academics from a variety of fields were interviewed. The core of the semi-structured interviews focused on participants' own work-related experiences that could be recalled and discussed in depth. This research validated and augmented prior research while consolidating previous models of serendipity into a single model of the process of serendipity, consisting of: Trigger, Connection, Follow-up, and Valuable Outcome, and an Unexpected Thread that runs through 1 or more of the first 4 elements. Together, the elements influence the Perception of Serendipity. Furthermore, this research identified what factors relating to the individual and their environment may facilitate the main elements of serendipity and further influence its perception.},
language = {en},
number = {7},
urldate = {2021-12-29},
journal = {Journal of the Association for Information Science and Technology},
author = {McCay-Peet, Lori and Toms, Elaine G.},
year = {2015},
note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/asi.23273},
keywords = {information models, qualitative research},
pages = {1463--1476},
file = {McCay-Peet_Toms_2015_Investigating_serendipity.pdf:files/7169/McCay-Peet_Toms_2015_Investigating_serendipity.pdf:application/pdf;Snapshot:files/7170/asi.html:text/html},
}
@article{drago_possibility_1999,
title = {Possibility and {Necessity} {Pattern} {Classification} using an {Interval} {Arithmetic} {Perceptron}},
volume = {8},
issn = {1433-3058},
url = {https://doi.org/10.1007/s005210050006},
doi = {10.1007/s005210050006},
abstract = {In the work presented in this paper, an Interval Arithmetic Perceptron (IAP) is used to detect the region in the input space to which an uncertainty decision should be appropriately associated. This region may be originated both by sub-regions which are not represented in the training set, and by subregions where the probabilities of the two classes are very similar. To train the IAP, an algorithm will be presented which in particular is able detect the two certainty regions and the uncertainty one From the interval weights thus obtained, a confidence interval of the probability will also be evaluated. The algorithm has been used for studying a simple artificial problem and two real-world appli-cations, the Iris and Breast Cancer databases. Regarding the latter application in particular, a statistical analysis of the results is presented, together with a discussion of the possible alternative classifications of the patterns attributed to the uncertainty region.},
language = {en},
number = {1},
urldate = {2021-12-31},
journal = {Neural Computing \& Applications},
author = {Drago, G.P. and Ridella, S.},
month = mar,
year = {1999},
pages = {40--52},
file = {Drago_Ridella_1999_Possibility_and_Necessity_Pattern_Classification_using_an_Interval_Arithmetic.pdf:files/7172/Drago_Ridella_1999_Possibility_and_Necessity_Pattern_Classification_using_an_Interval_Arithmetic.pdf:application/pdf},
}
@article{ishibuchi_possibility_1992,
title = {Possibility and necessity pattern classification using neural networks},
volume = {48},
issn = {0165-0114},
url = {https://www.sciencedirect.com/science/article/pii/0165011492903488},
doi = {10.1016/0165-0114(92)90348-8},
abstract = {We propose two learning algorithms of neural networks for two-group discriminant problems from the view point of possibility and necessity. One algorithm corresponds to the possibility analysis and the other to the necessity analysis. The proposed algorithms are similar to the back-propagation algorithm and the difference stems from a formulation of a cost function to be minimized in each algorithm. Each cost function of the proposed algorithms is the weighted sum of squared errors, that is, the sum of squared errors with different penalties. When we discuss the possibility of Group 1, the penalty for the squared errors relating to the patterns in Group 1 is greater than that of Group 2. This means that, in the possibility analysis of Group 1, we attach greater importance to the patterns in Group 1 than to those in Group 2. On the other hand, when we discuss the necessity of Group 1, the penalty for the squared errors relating to the patterns in Group 2 is greater than that of Group 1.},
language = {en},
number = {3},
urldate = {2021-12-31},
journal = {Fuzzy Sets and Systems},
author = {Ishibuchi, Hisao and Fujioka, Ryosuke and Tanaka, Hideo},
month = jun,
year = {1992},
keywords = {Neural networks, approximate classification, back-propagation algorithm, pattern recognition, possibility and necessity},
pages = {331--340},
file = {Ishibuchi_et_al_1992_Possibility_and_necessity_pattern_classification_using_neural_networks.pdf:files/7174/Ishibuchi_et_al_1992_Possibility_and_necessity_pattern_classification_using_neural_networks.pdf:application/pdf},
}
@article{negri_partial_2013,
title = {Partial {Probability} and {Kleene} {Logic}},
url = {http://arxiv.org/abs/1310.6172},
abstract = {There are two main approach to probability, one of set-theoretic character where probability is the measure of a set, and another one of linguistic character where probability is the degree of confidence in a proposition. In this work we give an unified algebraic treatment of these approaches through the concept of valued lattice, obtaining as a by-product a translation between them. Then we introduce the concept of partial valuation for DMF-algebras (De Morgan algebras with a single fixed point for negation), giving an algebraic setting for probability of partial events. We introduce the concept of partial probability for propositions, substituting classical logic with Kleene's logic. In this case too we give a translation between set-theoretic and linguistic probability. Finally, we introduce the concept of conditional partial probability and prove a weak form of Bayes's Theorem.},
urldate = {2021-12-31},
journal = {arXiv:1310.6172 [math]},
author = {Negri, Maurizio},
month = oct,
year = {2013},
note = {arXiv: 1310.6172},
keywords = {03G10, 60B99, 03B50, 06D25, Mathematics - Logic},
file = {arXiv.org Snapshot:files/7177/1310.html:text/html;Negri_2013_Partial_Probability_and_Kleene_Logic.pdf:files/7176/Negri_2013_Partial_Probability_and_Kleene_Logic.pdf:application/pdf},
}
@article{ciucci_borderline_2014,
series = {Weighted {Logics} for {Artificial} {Intelligence}},
title = {Borderline vs unknown: comparing three-valued representations of imperfect information},
volume = {55},
issn = {0888-613X},
shorttitle = {Borderline vs. unknown},
url = {https://www.sciencedirect.com/science/article/pii/S0888613X14001157},
doi = {10.1016/j.ijar.2014.07.004},
abstract = {In this paper we compare the expressive power of elementary representation formats for vague, incomplete or conflicting information. These include Boolean valuation pairs introduced by Lawry and González-Rodríguez, orthopairs of sets of variables, Boolean possibility and necessity measures, three-valued valuations, supervaluations. We make explicit their connections with strong Kleene logic and with Belnap logic of conflicting information. The formal similarities between 3-valued approaches to vagueness and formalisms that handle incomplete information often lead to a confusion between degrees of truth and degrees of uncertainty. Yet there are important differences that appear at the interpretive level: while truth-functional logics of vagueness are accepted by a part of the scientific community (even if questioned by supervaluationists), the truth-functionality assumption of three-valued calculi for handling incomplete information looks questionable, compared to the non-truth-functional approaches based on Boolean possibility–necessity pairs. This paper aims to clarify the similarities and differences between the two situations. We also study to what extent operations for comparing and merging information items in the form of orthopairs can be expressed by means of operations on valuation pairs, three-valued valuations and underlying possibility distributions.},
language = {en},
number = {9},
urldate = {2021-12-31},
journal = {International Journal of Approximate Reasoning},
author = {Ciucci, Davide and Dubois, Didier and Lawry, Jonathan},
month = dec,
year = {2014},
keywords = {Belnap logic, Incomplete information, Kleene logic, Orthopairs, Partial models, Supervaluations, Vagueness},
pages = {1866--1889},
file = {Ciucci_et_al_2014_Borderline_vs_unknown.pdf:files/7179/Ciucci_et_al_2014_Borderline_vs_unknown.pdf:application/pdf},
}
@article{peykani_novel_2018,
title = {A {Novel} {Fuzzy} {Data} {Envelopment} {Analysis} {Based} on {Robust} {Possibilistic} {Programming}: {Possibility}, {Necessity} and {Credibility}-{Based} {Approaches}},
volume = {52},
shorttitle = {A {Novel} {Fuzzy} {Data} {Envelopment} {Analysis} {Based} on {Robust} {Possibilistic} {Programming}},
doi = {10.1051/ro/2018019},
abstract = {Possibilistic programming approach is one of the most popular methods used to cope with epistemic uncertainty in optimization models. In this paper, several robust fuzzy data envelopment analysis (RFDEA) models are proposed by the use of different fuzzy measures including possibility, necessity and credibility measures. Despite the regular fuzzy DEA methods, the proposed models are able to endogenously adjust the confidence level of each constraints and produce both conservative and non-conservative methods based on various fuzzy measures. The developed RFDEA models are then linearized and numerically compared to regular fuzzy DEA models. Illustrative results in all of the FDEA and RFDEA models show that, maximum efficiency is obtained for possibility, credibility and necessity-based models, respectively.},
journal = {RAIRO - Operations Research},
author = {Peykani, Pejman and Mohammadi, Emran and Pishvaee, Mir and Rostamy-Malkhalifeh, Mohsen and Jabbarzadeh, Armin},
month = dec,
year = {2018},
pages = {1445--1463},
file = {Peykani_et_al_2018_A_Novel_Fuzzy_Data_Envelopment_Analysis_Based_on_Robust_Possibilistic.pdf:files/7181/Peykani_et_al_2018_A_Novel_Fuzzy_Data_Envelopment_Analysis_Based_on_Robust_Possibilistic.pdf:application/pdf},
}
@article{jung_structure_2013,
title = {The structure of creative cognition in the human brain},
volume = {7},
issn = {1662-5161},
url = {https://www.frontiersin.org/article/10.3389/fnhum.2013.00330},
doi = {10.3389/fnhum.2013.00330},
abstract = {Creativity is a vast construct, seemingly intractable to scientific inquiry—perhaps due to the vague concepts applied to the field of research. One attempt to limit the purview of creative cognition formulates the construct in terms of evolutionary constraints, namely that of blind variation and selective retention (BVSR). Behaviorally, one can limit the “blind variation” component to idea generation tests as manifested by measures of divergent thinking. The “selective retention” component can be represented by measures of convergent thinking, as represented by measures of remote associates. We summarize results from measures of creative cognition, correlated with structural neuroimaging measures including structural magnetic resonance imaging (sMRI), diffusion tensor imaging (DTI), and proton magnetic resonance spectroscopy (1H-MRS). We also review lesion studies, considered to be the “gold standard” of brain-behavioral studies. What emerges is a picture consistent with theories of disinhibitory brain features subserving creative cognition, as described previously (Martindale, 1981). We provide a perspective, involving aspects of the default mode network (DMN), which might provide a “first approximation” regarding how creative cognition might map on to the human brain.},
urldate = {2022-01-01},
journal = {Frontiers in Human Neuroscience},
author = {Jung, Rex and Mead, Brittany and Carrasco, Jessica and Flores, Ranee},
year = {2013},
pages = {330},
file = {Jung et al_2013_The structure of creative cognition in the human brain.pdf:files/7186/Jung et al_2013_The structure of creative cognition in the human brain.pdf:application/pdf;Jung_et_al_2013_The_structure_of_creative_cognition_in_the_human_brain.pdf:files/7227/Jung_et_al_2013_The_structure_of_creative_cognition_in_the_human_brain.pdf:application/pdf},
}
@book{sawyer_creativity_2003,
title = {Creativity and {Development}},
isbn = {978-0-19-514900-5},
abstract = {What is creativity, and where does it come from? Creativity and Development explores the fascinating connections and tensions between creativity research and developmental psychology, two fields that have largely progressed independently of each other-until now. In this book, scholars influential in both fields explore the emergence of new ideas, and the development of the people and situations that bring them to fruition. The uniquely collaborative nature of Oxford's Counterpoints series allows them to engage in a dialogue, addressing the key issues and potential benefits of exploring the connections between creativity and development. Creativity and Development is based on the observation that both creativity and development are processes that occur in complex systems, in which later stages or changes emerge from the prior state of the system. In the 1970s and 1980s, creativity researchers shifted their focus from personality traits to cognitive and social processes, and the co-authors of this volume are some of the most influential figures in this shift. The central focus on system processes results in three related volume themes: how the outcomes of creativity and development emerge from dynamical processes, the interrelation between individual processes and social processes, and the role of mediating artifacts and domains in developmental and creative processes. The chapters touch on a wide range of important topics, with the authors drawing on their decades of research into creativity and development. Readers will learn about the creativity of children's play, the creative aspects of children's thinking, the creative processes of scientists, the role of education and teaching in creative development, and the role of multiple intelligences in both creativity and development. The final chapter is an important dialogue between the authors, who engage in a roundtable discussion and explore key questions facing contemporary researchers, such as: Does society suppress children's creativity? Are creativity and development specific to an intelligence or a domain? What role do social and cultural contexts play in creativity and development? Creativity and Development presents a powerful argument that both creativity scholars and developmental psychologists will benefit by becoming more familiar with each other's work.},
language = {en},
publisher = {Oxford University Press},
author = {Sawyer, Robert Keith and John-Steiner, Vera and Moran, Seana and Sternberg, Robert J. and Feldman, David Henry and Csikszentmihalyi, Mihaly and Gardner, Howard and Nakamura, Jeanne},
year = {2003},
note = {Google-Books-ID: TWdnDAAAQBAJ},
keywords = {Psychology / Developmental / Child, Psychology / Developmental / General, Psychology / Creative Ability, Psychology / Social Psychology},
}
@article{zander_intuition_2016,
title = {Intuition and {Insight}: {Two} {Processes} {That} {Build} on {Each} {Other} or {Fundamentally} {Differ}?},
volume = {7},
issn = {1664-1078},
shorttitle = {Intuition and {Insight}},
url = {https://www.frontiersin.org/article/10.3389/fpsyg.2016.01395},
doi = {10.3389/fpsyg.2016.01395},
abstract = {Intuition and insight are intriguing phenomena of non-analytical mental functioning: whereas intuition denotes ideas that have been reached by sensing the solution without any explicit representation of it, insight has been understood as the sudden and unexpected apprehension of the solution by recombining the single elements of a problem. By face validity, the two processes appear similar; according to a lay perspective, it is assumed that intuition precedes insight. Yet, predominant scientific conceptualizations of intuition and insight consider the two processes to differ with regard to their (dis-)continuous unfolding. That is, intuition has been understood as an experience-based and gradual process, whereas insight is regarded as a genuinely discontinuous phenomenon. Unfortunately, both processes have been investigated differently and without much reference to each other. In this contribution, we therefore set out to fill this lacuna by examining the conceptualizations of the assumed underlying cognitive processes of both phenomena, and by also referring to the research traditions and paradigms of the respective field. Based on early work put forward by Bowers et al. (1990, 1995), we referred to semantic coherence tasks consisting of convergent word triads (i.e., the solution has the same meaning to all three clue words) and/or divergent word triads (i.e., the solution means something different with respect to each clue word) as an excellent kind of paradigm that may be used in the future to disentangle intuition and insight experimentally. By scrutinizing the underlying mechanisms of intuition and insight, with this theoretical contribution, we hope to launch lacking but needed experimental studies and to initiate scientific cooperation between the research fields of intuition and insight that are currently still separated from each other.},
urldate = {2022-01-02},
journal = {Frontiers in Psychology},
author = {Zander, Thea and Öllinger, Michael and Volz, Kirsten G.},
year = {2016},
pages = {1395},
file = {Zander_et_al_2016_Intuition_and_Insight.pdf:files/7190/Zander_et_al_2016_Intuition_and_Insight.pdf:application/pdf},
}
@inproceedings{ritchie_closer_2012,
title = {A closer look at creativity as search},
url = {https://www.academia.edu/5626724/A_closer_look_at_creativity_as_search},
abstract = {A closer look at creativity as search},
language = {en},
urldate = {2022-01-02},
booktitle = {Proceedings of the {Third} {International} {Conference} on {Computational} {Creativity}},
author = {Ritchie, Graeme},
month = may,
year = {2012},
file = {Ritchie_2012_A_closer_look_at_creativity_as_search.pdf:files/7400/Ritchie_2012_A_closer_look_at_creativity_as_search.pdf:application/pdf;Snapshot:files/7192/A_closer_look_at_creativity_as_search.html:text/html},
}
@article{wiggins_preliminary_2006,
series = {Creative {Systems}},
title = {A preliminary framework for description, analysis and comparison of creative systems},
volume = {19},
issn = {0950-7051},
url = {https://www.sciencedirect.com/science/article/pii/S0950705106000645},
doi = {10.1016/j.knosys.2006.04.009},
abstract = {I summarise and attempt to clarify some concepts presented in and arising from Margaret Boden’s (1990) descriptive hierarchy of creativity, by beginning to formalise the ideas she proposes. The aim is to move towards a model which allows detailed comparison, and hence better understanding, of systems which exhibit behaviour which would be called “creative” in humans. The work paves the way for the description of naturalistic, multi-agent creative AI systems, which create in a societal context.I demonstrate some simple reasoning about creative behaviour based on the new framework, to show how it might be useful for the analysis and study of creative systems. In particular, I identify some crucial properties of creative systems, in terms of the framework components, some of which may usefully be proven a priori of a given system.I suggest that Boden’s descriptive framework, once elaborated in detail, is more uniform and more powerful than it first appears.},
language = {en},
number = {7},
journal = {Knowledge-Based Systems},
author = {Wiggins, Geraint A.},
month = nov,
year = {2006},
pages = {449--458},
file = {ScienceDirect Snapshot:files/7398/S0950705106000645.html:text/html;Wiggins - 2006 - A preliminary framework for description, analysis .pdf:files/7397/Wiggins - 2006 - A preliminary framework for description, analysis .pdf:application/pdf},
}
@techreport{vieville_improved_2002,
type = {report},
title = {An improved biologically plausible trajectory generator},
url = {https://hal.inria.fr/inria-00072049},
abstract = {Considering the biological or artificial control of a trajectory generation, we propose a biologically plausible model based on harmonic potentials. Such methods assume that obstacles to avoid (or constraints not to violate) correspond to maxima of the potential, while the goal corresponds to a unique minimum. The corresponding algorithm thus behaves as if one throws a sheet onto this state space, this hyper-surface relief being elevated on obstacles, with a hole at the goal location, so that finding a trajectory reduces to «roll down» along this relief towards the minimal height location. The originality of the present work is to build an harmonic potential (thus without local minimum) as a finite linear combination of elementary harmonic functions. The set of these components samples the border of the admissible domain bounded by obstacles or constraints. This leads to an internal representation of the problem as a non-topographical map increment- ally builded during the system exploration and non-linearly linked to the real problem geometry. As such, it provides a biologically plausible quantitative model of some hippocampus mechanisms and of the related cognitive maps, in coherence with usual biological assumptions about such behavior.},
language = {en},
urldate = {2022-01-05},
institution = {INRIA},
author = {Viéville, Thierry},
month = sep,
year = {2002},
file = {Snapshot:files/7200/inria-00072049.html:text/html;Vieville_2002_An_improved_biologically_plausible_trajectory_generator.pdf:files/7199/Vieville_2002_An_improved_biologically_plausible_trajectory_generator.pdf:application/pdf},
}
@article{basantia_culture_2017,
title = {Culture, {Value} and {Personality}: {Three} {Flowering} {Agents} of {Creativity} {Development} {Process}},
volume = {5},
copyright = {© 2017 Science and Education Publishing},
issn = {2333-472X},
shorttitle = {Culture, {Value} and {Personality}},
url = {http://pubs.sciepub.com/ajap/5/1/1/index.html},
doi = {10.12691/ajap-5-1-1},
abstract = {‘Creativity’ is a unique gift of God to Mankind. The prosperity of an individual in one hand and the prosperity of a family, community, nation and the world at large in other hand mostly rest on this creativity. Basically, creativity is a psychological construct and this psychological construct is mainly characterized by non-conformity or uniqueness. Creativity never develops in vacuum. The creativity development process is influenced by a number of psycho-social factors or agents. Among the agents which flower or help the creativity development process, the role of three agents i.e. culture, value and personality is quite significant. Referring to these contexts, in the present paper mainly discussions have been made on defining aspect of creativity and the role of culture, value and personality on creativity development process.},
language = {en},
number = {1},
urldate = {2022-01-10},
journal = {American Journal of Applied Psychology},
author = {Basantia, Tapan Kumar},
month = jan,
year = {2017},
note = {Number: 1
Publisher: Science and Education Publishing},
pages = {1--6},
file = {Basantia_2017_Culture, Value and Personality.pdf:files/7205/Basantia_2017_Culture, Value and Personality.pdf:application/pdf;Snapshot:files/7206/index.html:text/html},
}
@misc{noauthor_document_nodate,
title = {Document sans titre},
url = {https://docs.google.com/document/u/0/d/1AItngxaXy3WpkJTgYgYN4nuZVAVvIX6s2yh3a7mU9yE/edit?usp=embed_facebook},
language = {fr},
urldate = {2022-01-10},
journal = {Google Docs},
file = {Snapshot:files/7208/edit.html:text/html},
}
@inproceedings{janowicz_stimulus-sensor-observation_2010,
address = {Aachen, DEU},
series = {{SSN}'10},
title = {The {Stimulus}-{Sensor}-{Observation} {Ontology} {Design} {Pattern} and its {Integration} into the {Semantic} {Sensor} {Network} {Ontology}},
abstract = {This paper presents an overview of ongoing work to develop a generic ontology design pattern for observation-based data on the Semantic Web. The core classes and relationships forming the pattern are discussed in detail and are aligned to the DOLCE foundational ontology to improve semantic interoperability and clarify the underlying ontological commitments. The pattern also forms the top-level of the the Semantic Sensor Network ontology developed by the W3C Semantic Sensor Network Incubator Group. The integration of both ontologies is discussed and directions of further work are pointed out.},
urldate = {2022-01-14},
booktitle = {Proceedings of the 3rd {International} {Conference} on {Semantic} {Sensor} {Networks} - {Volume} 668},
publisher = {CEUR-WS.org},
author = {Janowicz, Krzysztof and Compton, Michael},
month = nov,
year = {2010},
pages = {64--78},
file = {Janowicz_Compton_The_Stimulus-Sensor-Observation_Ontology_Design_Pattern_and_its_Integration.pdf:files/7224/Janowicz_Compton_The_Stimulus-Sensor-Observation_Ontology_Design_Pattern_and_its_Integration.pdf:application/pdf},
}
@inproceedings{tubb_four_2014,
title = {A {Four} {Strategy} {Model} of {Creative} {Parameter} {Space} {Interaction}},
abstract = {A new theoretical model for the design of creativity-enhancing interfaces is proposed, which predicts that the majority of computer interfaces provide separate parameters, altered sequentially and predicts that these oneto-one mappings encourage a particular navigation strategy (“Explicit-Convergent”) and as such may inhibit certain aspects of creativity. This paper proposes a new theoretical model for the design of creativity-enhancing interfaces. The combination of user and content creation software is looked at as a creative system, and we tackle the question of how best to design the interface to utilise the abilities of both the computer and the brain. This model has been developed in the context of music technology, but may apply to any situation in which a large number of feature parameters must be adjusted to achieve a creative result. The model of creativity inspiring this approach is Wiggins’ Creative Systems Framework. Two further theories from cognitive psychology motivate the model: the notion of creativity being composed of divergent and convergent thought processes, and the “dual process” theory of implicit vs. explicit thought. These two axes are combined to describe four different solution space traversal strategies. The majority of computer interfaces provide separate parameters, altered sequentially. This theory predicts that these oneto-one mappings encourage a particular navigation strategy (“Explicit-Convergent”) and as such may inhibit certain aspects of creativity.},
booktitle = {{ICCC}},
author = {Tubb, Robert and Dixon, S.},
year = {2014},
}
@article{dietrich_neurocognitive_2017,
title = {A {Neurocognitive} {Framework} for {Human} {Creative} {Thought}},
volume = {7},
issn = {1664-1078},
url = {https://www.frontiersin.org/article/10.3389/fpsyg.2016.02078},
doi = {10.3389/fpsyg.2016.02078},
abstract = {We are an intensely creative species. Creativity is the fountainhead of our civilizations and a defining characteristic of what makes us human. But for all its prominence at the apex of human mental faculties, we know next to nothing about how brains generate creative ideas. With all previous attempts to tighten the screws on this vexed problem unsuccessful – right brains, divergent thinking, defocused attention, default mode network, alpha enhancement, prefrontal activation, etc. (Dietrich and Kanso, 2010) – the neuroscientific study of creativity finds itself in a theoretical arid zone that has perhaps no equal in psychology. We propose here a general framework for a fresh attack on the problem and set it out under 10 foundational concepts. Most of the ideas we favor are part and parcel of the standard conceptual toolbox of cognitive neuroscience but their combination and significance to creativity are original. By outlining, even in such broad strokes, the theoretical landscape of cognitive neuroscience as it relates to creative insights, we hope to bring into clear focus the key enabling factors that are likely to have a hand in computing ideational combinations in the brain.},
urldate = {2021-12-20},
journal = {Frontiers in Psychology},
author = {Dietrich, Arne and Haider, Hilde},
year = {2017},
pages = {2078},
file = {Dietrich_Haider_2017_A Neurocognitive Framework for Human Creative Thought.pdf:files/7157/Dietrich_Haider_2017_A Neurocognitive Framework for Human Creative Thought.pdf:application/pdf;Dietrich_Haider_2017_A_Neurocognitive_Framework_for_Human_Creative_Thought.pdf:files/7239/Dietrich_Haider_2017_A_Neurocognitive_Framework_for_Human_Creative_Thought.pdf:application/pdf},
}
@article{de_grave_problem_1996,
title = {Problem based learning: {Cognitive} and metacognitive processes during problem analysis},
volume = {24},
issn = {1573-1952},
shorttitle = {Problem based learning},
url = {https://doi.org/10.1007/BF00118111},
doi = {10.1007/BF00118111},
abstract = {An important phase of problem-based learning in a tutorial group is problem analysis. This article describes a study investigating the ongoing cognitive and metacognitive processes during problem analysis, by analysing the verbal communication among group members, and their thinking processes. Thinking processes were tapped by means of a stimulated recall procedure. Verbatim transcripts of both the verbal interaction in the group and the recall protocols were analysed. The goal of this research is two-fold, i.e., to investigate whether PBL indeed leads to conceptual change and to develop a method that is sensitive to these phenomena.},
language = {en},
number = {5},
urldate = {2022-01-14},
journal = {Instructional Science},
author = {De Grave, W. S. and Boshuizen, H. P. A. and Schmidt, H. G.},
month = sep,
year = {1996},
pages = {321--341},
file = {De_Grave_et_al_1996_Problem_based_learning.pdf:files/7228/De_Grave_et_al_1996_Problem_based_learning.pdf:application/pdf},
}
@book{guilford_nature_1967,
address = {New York, NY, US},
series = {The nature of human intelligence},
title = {The nature of human intelligence},
abstract = {A thorough presentation of the factor-analytic model of intelligence with emphasis on the construction of tests to be used as input to the statistical analysis. Harvard Book List (edited) 1971 \#112 (PsycINFO Database Record (c) 2016 APA, all rights reserved)},
publisher = {McGraw-Hill},
author = {Guilford, J.P.},
year = {1967},
file = {Snapshot:files/7233/1967-35015-000.html:text/html},
}
@article{cowan_what_2008,
title = {What are the differences between long-term, short-term, and working memory?},
volume = {169},
issn = {0079-6123},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2657600/},
doi = {10.1016/S0079-6123(07)00020-9},
abstract = {In the recent literature there has been considerable confusion about the three types of memory: long-term, short-term, and working memory. This chapter strives to reduce that confusion and makes up-to-date assessments of these types of memory. Long- and short-term memory could differ in two fundamental ways, with only short-term memory demonstrating (1) temporal decay and (2) chunk capacity limits. Both properties of short-term memory are still controversial but the current literature is rather encouraging regarding the existence of both decay and capacity limits. Working memory has been conceived and defined in three different, slightly discrepant ways: as short-term memory applied to cognitive tasks, as a multi-component system that holds and manipulates information in short-term memory, and as the use of attention to manage short-term memory. Regardless of the definition, there are some measures of memory in the short term that seem routine and do not correlate well with cognitive aptitudes and other measures (those usually identified with the term “working memory”) that seem more attention demanding and do correlate well with these aptitudes. The evidence is evaluated and placed within a theoretical framework depicted in .},
urldate = {2022-01-14},
journal = {Progress in brain research},
author = {Cowan, Nelson},
year = {2008},
pmid = {18394484},
pmcid = {PMC2657600},
pages = {323--338},
file = {Cowan_2008_What_are_the_differences_between_long-term,_short-term,_and_working_memory.pdf:files/7234/Cowan_2008_What_are_the_differences_between_long-term,_short-term,_and_working_memory.pdf:application/pdf},
}
@article{cowan_sensory_2010,
title = {Sensory and {Immediate} {Memory}},
doi = {10.1016/B978-012373873-8.00048-7},
abstract = {Sensory memory is recollection of perceptual types of how a stimulus looks, feels, sounds, etc. Immediate memory (including, but not limited to, sensory memory) is recollection of a small amount of information for a brief time; it is used to carry out cognitive tasks. Two key immediate-memory mechanisms are (1) activated sensory and conceptual features from long-term memory, with a short time limit to this activation; and (2) the subset of activated information that is in the focus of attention, with a limit to how many items can be in focus at once. These memory mechanisms may underlie conscious phenomena like the perceptual moment and the psychological present.},
journal = {Encyclopedia of Consciousness},
author = {Cowan, Nelson},
month = jan,
year = {2010},
}
@article{mandler_spatial_2010,
title = {The spatial foundations of the conceptual system},
volume = {2},
doi = {10.1515/LANGCOG.2010.002},
abstract = {This article proposes that the representation of concepts in infancy is in the form of spatial image-schemas. A mechanism that simplifies spatial infor-mation is described along with a small set of spatial primitives that are suf-ficient to account for the conceptualizations that preverbal infants use to interpret objects and events. This early system is important to understand because it organizes the adult conceptual system of objects and events and remains its core. With development, the system becomes enriched by lan-guage in several ways, and also by means of analogical extension to non-spatial information. Nonspatial bodily information, such as feelings of force and motor activity, is also added, but remains secondary. It becomes asso-ciated with spatial representations, but except for its spatial aspects is rep-resented in a more inchoate and less accessible fashion.},
journal = {Language and Cognition},
author = {Mandler, Jean},
month = mar,
year = {2010},
file = {Mandler_2010_The_spatial_foundations_of_the_conceptual_system.pdf:files/7241/Mandler_2010_The_spatial_foundations_of_the_conceptual_system.pdf:application/pdf},
}
@article{beaty_creative_2016,
title = {Creative {Cognition} and {Brain} {Network} {Dynamics}},
volume = {20},
issn = {1879-307X},
doi = {10.1016/j.tics.2015.10.004},
abstract = {Creative thinking is central to the arts, sciences, and everyday life. How does the brain produce creative thought? A series of recently published papers has begun to provide insight into this question, reporting a strikingly similar pattern of brain activity and connectivity across a range of creative tasks and domains, from divergent thinking to poetry composition to musical improvisation. This research suggests that creative thought involves dynamic interactions of large-scale brain systems, with the most compelling finding being that the default and executive control networks, which can show an antagonistic relation, tend to cooperate during creative cognition and artistic performance. These findings have implications for understanding how brain networks interact to support complex cognitive processes, particularly those involving goal-directed, self-generated thought.},
language = {eng},
number = {2},
journal = {Trends in Cognitive Sciences},
author = {Beaty, Roger E. and Benedek, Mathias and Silvia, Paul J. and Schacter, Daniel L.},
month = feb,
year = {2016},
pmid = {26553223},
pmcid = {PMC4724474},
keywords = {networks, Humans, Creativity, Thinking, Cognition, creativity, Neural Pathways, Brain, imagination, connectivity, expertise, improvisation},
pages = {87--95},
file = {Beaty_et_al_2016_Creative_Cognition_and_Brain_Network_Dynamics.pdf:files/7245/Beaty_et_al_2016_Creative_Cognition_and_Brain_Network_Dynamics.pdf:application/pdf},
}
@article{kounios_cognitive_2014,
title = {The {Cognitive} {Neuroscience} of {Insight}},
volume = {65},
doi = {10.1146/annurev-psych-010213-115154},
abstract = {Insight occurs when a person suddenly reinterprets a stimulus, situation, or event to produce a nonobvious, nondominant interpretation. This can take the form of a solution to a problem (an "aha moment"), comprehension of a joke or metaphor, or recognition of an ambiguous percept. Insight research began a century ago, but neuroimaging and electrophysiological techniques have been applied to its study only during the past decade. Recent work has revealed insight-related coarse semantic coding in the right hemisphere and internally focused attention preceding and during problem solving. Individual differences in the tendency to solve problems insightfully rather than in a deliberate, analytic fashion are associated with different patterns of resting-state brain activity. Recent studies have begun to apply direct brain stimulation to facilitate insight. In sum, the cognitive neuroscience of insight is an exciting new area of research with connections to fundamental neurocognitive processes.},
journal = {Annual review of psychology},
author = {Kounios, John and Beeman, Mark},
month = jan,
year = {2014},
pages = {71--93},
file = {Kounios_Beeman_2014_The Cognitive Neuroscience of Insight.pdf:files/7247/Kounios_Beeman_2014_The Cognitive Neuroscience of Insight.pdf:application/pdf},
}
@article{widdows_reasoning_2014,
title = {Reasoning with {Vectors}: {A} {Continuous} {Model} for {Fast} {Robust} {Inference}},
shorttitle = {Reasoning with {Vectors}},
doi = {10.1093/jigpal/jzu028},
abstract = {See http://jigpal.oxfordjournals.org/content/early/2014/12/03/jigpal.jzu028.short
This article describes the use of continuous vector space models for reasoning with a formal knowledge base. The practical significance of these models is that they support fast, approximate but robust inference and hypothesis generation, which is complementary to the slow, exact, but sometimes brittle behaviour of more traditional deduction engines such as theorem provers.
The article explains the way logical connectives can be used in semantic vector models, and summarizes the development of Predication-based Semantic Indexing, which involves the use of Vector Symbolic Architectures to represent the concepts and relationships from a knowledge base of subject-predicate-object triples. Experiments show that the use of continuous models for formal reasoning is not only possible, but already demonstrably effective for some recognized informatics tasks, and showing promise in other traditional problem areas. Examples described in this article include: predicting new uses for existing drugs in biomedical informatics; removing unwanted meanings from search results in information retrieval and concept navigation; type inference from attributes; comparing words based on their orthography; and representing tabular data, including modelling numerical values.
The algorithms and techniques described in this article are all publicly released and freely available in the Semantic Vectors open-source software package.1},
journal = {Logic Journal of IGPL},
author = {Widdows, Dominic and Cohen, Trevor},
month = nov,
year = {2014},
file = {Widdows_Cohen_2014_Reasoning with Vectors.pdf:files/7253/Widdows_Cohen_2014_Reasoning with Vectors.pdf:application/pdf},
}
@book{heiser_analyse_2022,
title = {Analyse des activités technocréatives au collège en contexte d’éducation {FabLab}},
abstract = {Analyse des activités technocréatives au collège en contexte d'éducation FabLab Décembre 2021},
author = {Heiser, Laurent and Romero, Margarida and Prokofieva Nelson, Victoria},
month = jan,
year = {2022},
file = {Heiser_et_al_2022_Analyse_des_activites_technocreatives_au_college_en_contexte_d’education_FabLab.pdf:files/7256/Heiser_et_al_2022_Analyse_des_activites_technocreatives_au_college_en_contexte_d’education_FabLab.pdf:application/pdf},
}
@article{toyoshima_foundations_2020,
title = {Foundations for an {Ontology} of {Belief}, {Desire} and {Intention}},
url = {https://ebooks.iospress.nl/doi/10.3233/FAIA200667},
doi = {10.3233/FAIA200667},
abstract = {Belief, desire, and intention are central notions in mentality and agency. We provide conceptual and formal foundations for an ontology of those mental entities. In this framework, beliefs and desires have a dual face: dispositional and occurrent. As distinct from beliefs and desires, intentions are dispositions to actions that emerge from a decision process in which occurrent beliefs and occurrent desires interact. We also discuss how our theory can be extended to some major philosophical accounts of desires, and cognitive biases such as wishful thinking.},
language = {en},
urldate = {2022-01-26},
journal = {Formal Ontology in Information Systems},
author = {Toyoshima, Fumiaki and Barton, Adrien and Grenier, Olivier},
year = {2020},
note = {Publisher: IOS Press},
pages = {140--154},
file = {Snapshot:files/7260/55801.html:text/html;Toyoshima_et_al_2020_Foundations_for_an_Ontology_of_Belief,_Desire_and_Intention.pdf:files/7261/Toyoshima_et_al_2020_Foundations_for_an_Ontology_of_Belief,_Desire_and_Intention.pdf:application/pdf},
}
@article{hastings_representing_2012,
title = {Representing {Mental} {Functioning}: {Ontologies} for {Mental} {Health} and {Disease}},
shorttitle = {Representing {Mental} {Functioning}},
url = {https://www.semanticscholar.org/paper/Representing-Mental-Functioning%3A-Ontologies-for-and-Hastings-Ceusters/b65a0ab5fdf277fcaf782ca59ac4bd510159d31b},
abstract = {Mental and behavioral disorders represent a significant portion of the public health burden in all countries. The human cost of these disorders is immense, yet treatment options for sufferers are currently limited, with many patients failing to respond sufficiently to available interventions and drugs. High quality ontologies facilitate data aggregation and comparison across different disciplines, and may therefore speed up the translation of primary research into novel therapeutics. Realism-based ontologies describe entities in reality and the relationships between them in such a way that once formulated in a suitable formal language the ontologies can be used for sophisticated automated reasoning applications. Reference ontologies can be applied across different contexts in which different, and often mutually incompatible, domain-specific vocabularies have traditionally been used. In this contribution we describe the Mental Functioning Ontology (MF) and Mental Disease Ontology (MD), two realism-based ontologies currently under development for the description of human mental functioning and disease. We describe the structure and upper levels of the ontologies and preliminary application scenarios, and identify some open questions.},
language = {en},
urldate = {2022-01-25},
journal = {undefined},
author = {Hastings, Janna and Ceusters, W. and Jensen, Mark and Mulligan, K. and Smith, Barry},
year = {2012},
file = {Hastings_et_al_2012_Representing_Mental_Functioning.pdf:files/7262/Hastings_et_al_2012_Representing_Mental_Functioning.pdf:application/pdf;Snapshot:files/7263/b65a0ab5fdf277fcaf782ca59ac4bd510159d31b.html:text/html},
}
@article{gobet_how_2019,
title = {How {Artificial} {Intelligence} {Can} {Help} {Us} {Understand} {Human} {Creativity}},
volume = {10},
issn = {1664-1078},
url = {https://www.frontiersin.org/article/10.3389/fpsyg.2019.01401},
abstract = {Recent years have been marked by important developments in artificial intelligence (AI). These developments have highlighted serious limitations in human rationality and shown that computers can be highly creative. There are also important positive outcomes for psychologists studying creativity. It is now possible to design entirely new classes of experiments that are more promising than the simple tasks typically used for studying creativity in psychology. In addition, given the current and future AI algorithms for developing new data structures and programs, novel theories of creativity are on the horizon. Thus, AI opens up entire new avenues for studying human creativity in psychology.},
urldate = {2022-02-03},
journal = {Frontiers in Psychology},
author = {Gobet, Fernand and Sala, Giovanni},
year = {2019},
file = {Gobet_Sala_2019_How_Artificial_Intelligence_Can_Help_Us_Understand_Human_Creativity.pdf:files/7265/Gobet_Sala_2019_How_Artificial_Intelligence_Can_Help_Us_Understand_Human_Creativity.pdf:application/pdf},
}
@article{newell_knowledge_1981,
title = {The {Knowledge} {Level}: {Presidential} {Address}},
volume = {2},
copyright = {Copyright (c)},
issn = {2371-9621},
shorttitle = {The {Knowledge} {Level}},
url = {https://ojs.aaai.org/index.php/aimagazine/article/view/99},
doi = {10.1609/aimag.v2i2.99},
abstract = {This is the first presidential address of AAAI, the American Association for Artificial Intelligence. In the grand scheme of history of artificial intelligence (AI), this is surely a minor event. The field this scientific society represents has been thriving for quite some time. No doubt the society itself will make solid contributions to the health of our field. But it is too much to expect a presidential address to have a major impact. So what is the role of the presidential address and what is the significance of the first one? I believe its role is to set a tone, to provide an emphasis. I think the role of the first address is to take a stand about what that tone and emphasis should be-set expectations for future addresses and to communicate to my fellow presidents. Only two foci are really possible for a presidential address: the state of the society or the state of the science. I believe the latter to be correct focus. AAAI itself, its nature and its relationship to the larger society that surrounds it, are surely important. However, our main business is to help AI become a science -- albeit a science with a strong engineering flavor. Thus, though a president's address cannot be narrow or highly technical, it can certainly address a substantive issue. That is what I propose to do.},
language = {en},
number = {2},
urldate = {2022-02-03},
journal = {AI Magazine},
author = {Newell, Allen},
month = sep,
year = {1981},
note = {Number: 2},
pages = {1--1},
file = {Newell_1981_The_Knowledge_Level.pdf:files/7269/Newell_1981_The_Knowledge_Level.pdf:application/pdf},
}
@article{pizlo_human_2006,
title = {Human {Problem} {Solving} - {An} {Extension} of {Newell} and {Simon}'s {Paradigm}},
abstract = {Several psychophysical studies on human problem solving were performed. These studies involved the following problems: the Traveling Salesman Problem, the 15-puzzle and variants of this puzzle with different sizes, and finally, the TSP with obstacles. All these problems are difficult combinatorial problems and are considered intractable. However, human subjects were found to produce near-optimal solutions very quickly. For all these problems, a pyramid algorithm was used as a model of the mental representation of the problem, and of the global-to-local process of producing the solution. This approach represents a paradigm shift in the study of human problem solving because the prior research (1) neglected mental representation of problems and (2) it concentrated on easy problems that are not solved well by humans. As a part of this project, a workshop on human problem solving was held at Purdue. After the workshop, a new journal was launched. This is the first journal dedicated to human problem solving.},
author = {Pizlo, Zygmunt},
month = oct,
year = {2006},
pages = {20},
file = {Pizlo_2006_Human_Problem_Solving_-_An_Extension_of_Newell_and_Simon's_Paradigm.pdf:files/7271/Pizlo_2006_Human_Problem_Solving_-_An_Extension_of_Newell_and_Simon's_Paradigm.pdf:application/pdf},
}
@article{gardenfors_conceptual_2004,
title = {Conceptual {Spaces} as a {Framework} for {Knowledge} {Representation}},
volume = {2},
abstract = {The dominating models of information processes have been based on symbolic representations of information and knowledge. During the last decades, a variety of non-symbolic models have been proposed as superior. The prime examples of models within the non-symbolic approach are neural networks. However, to a large extent they lack a higher-level theory of representation. In this paper, conceptual spaces are suggested as an appropriate framework for non- symbolic models. Conceptual spaces consist of a number of 'quality dimensions' that often are derived from perceptual mechanisms. It will be outlined how conceptual spaces can represent various kind of information and how they can be used to describe concept learning. The connections to prototype theory will also be presented.},
journal = {Mind and Matter},
author = {Gärdenfors, Peter},
month = jan,
year = {2004},
pages = {9--27},
file = {Gardenfors_2004_Conceptual_Spaces_as_a_Framework_for_Knowledge_Representation.pdf:files/7277/Gardenfors_2004_Conceptual_Spaces_as_a_Framework_for_Knowledge_Representation.pdf:application/pdf},
}
@inproceedings{boumaza_optimal_2007,
title = {Optimal control subsumes harmonic control},
url = {https://hal.inria.fr/inria-00170185},
abstract = {We consider trajectory planning within the frameworks of optimal control and harmonic control. We present a formal evidence, in continuous domain and in a standard discretization, that harmonic control is the limit case of a some optimal control problem in which we make the noise level tend to infinity. In other words we show that optimal control subsumes harmonic control. We discuss properties of both paradigms and present simulations that illustrate this relationship.},
language = {en},
urldate = {2022-02-03},
publisher = {IEEE},
author = {Boumaza, Amine and Scherrer, Bruno},
month = apr,
year = {2007},
pages = {2841},
file = {Boumaza_Scherrer_2007_Optimal_control_subsumes_harmonic_control.pdf:files/7280/Boumaza_Scherrer_2007_Optimal_control_subsumes_harmonic_control.pdf:application/pdf;Snapshot:files/7281/inria-00170185v1.html:text/html},
}
@article{webb_insight_2016,
title = {Insight {Is} {Not} in the {Problem}: {Investigating} {Insight} in {Problem} {Solving} across {Task} {Types}},
volume = {7},
issn = {1664-1078},
shorttitle = {Insight {Is} {Not} in the {Problem}},
url = {https://www.frontiersin.org/article/10.3389/fpsyg.2016.01424},
abstract = {The feeling of insight in problem solving is typically associated with the sudden realization of a solution that appears obviously correct (Kounios et al., 2006). Salvi et al. (2016) found that a solution accompanied with sudden insight is more likely to be correct than a problem solved through conscious and incremental steps. However, Metcalfe (1986) indicated that participants would often present an inelegant but plausible (wrong) answer as correct with a high feeling of warmth (a subjective measure of closeness to solution). This discrepancy may be due to the use of different tasks or due to different methods in the measurement of insight (i.e., using a binary vs. continuous scale). In three experiments, we investigated both findings, using many different problem tasks (e.g., Compound Remote Associates, so-called classic insight problems, and non-insight problems). Participants rated insight-related affect (feelings of Aha-experience, confidence, surprise, impasse, and pleasure) on continuous scales. As expected we found that, for problems designed to elicit insight, correct solutions elicited higher proportions of reported insight in the solution compared to non-insight solutions; further, correct solutions elicited stronger feelings of insight compared to incorrect solutions.},
urldate = {2022-02-03},
journal = {Frontiers in Psychology},
author = {Webb, Margaret E. and Little, Daniel R. and Cropper, Simon J.},
year = {2016},
file = {Webb_et_al_2016_Insight_Is_Not_in_the_Problem.pdf:files/7283/Webb_et_al_2016_Insight_Is_Not_in_the_Problem.pdf:application/pdf},
}
@article{kenett_semantic_2019,
title = {A {Semantic} {Network} {Cartography} of the {Creative} {Mind}},
volume = {23},
issn = {1364-6613},
url = {https://www.sciencedirect.com/science/article/pii/S1364661319300245},
doi = {10.1016/j.tics.2019.01.007},
abstract = {The role of semantic memory in creativity is theoretically assumed, but far from understood. In recent years, computational network science tools have been applied to investigate this role. These studies shed unique quantitative insights on the role of semantic memory structure in creativity, via measures of connectivity, distance, and structure.},
language = {en},
number = {4},
urldate = {2022-02-03},
journal = {Trends in Cognitive Sciences},
author = {Kenett, Yoed N. and Faust, Miriam},
month = apr,
year = {2019},
keywords = {Humans, Creativity, Semantics, Cognition, creativity, Memory, network science, semantic networks, Cognitive Science},
pages = {271--274},
file = {ScienceDirect Snapshot:files/7285/S1364661319300245.html:text/html},
}
@incollection{laird_soar_1986,
address = {Boston, MA},
series = {The {Kluwer} {International} {Series} in {Engineering} and {Computer} {Science}},
title = {Soar - {A} {General} {Problem}-{Solving} {Architecture}},
isbn = {978-1-4613-2277-1},
url = {https://doi.org/10.1007/978-1-4613-2277-1_15},
abstract = {Soar is a problem solving system that is based on formulating all activity (both problems and routine tasks) as heuristic search in problem spaces. A problem space consists of a set of states and a set of operators that transform one state into another. Starting from an initial state the problem solver applies a sequence of operators in an attempt to reach a desired state. Soar uses a production system1 to implement elementary operators, tests for goal satisfaction and failure, and search control — information relevant to the selection of goals, problem spaces, states, and operators. It is possible to use a problem space that has no search control, only operators and goal recognizers. Such a space will work correctly, but will be slow because of the amount of search required.},
language = {en},
urldate = {2022-02-05},
booktitle = {Universal {Subgoaling} and {Chunking}: {The} {Automatic} {Generation} and {Learning} of {Goal} {Hierarchies}},
publisher = {Springer US},
author = {Laird, John and Rosenbloom, Paul and Newell, Allen},
editor = {Laird, John and Rosenbloom, Paul and Newell, Allen},
year = {1986},
doi = {10.1007/978-1-4613-2277-1_15},
pages = {286--288},
file = {Springer Full Text PDF:files/7287/Laird et al. - 1986 - Soar—A General Problem-Solving Architecture.pdf:application/pdf},
}
@incollection{johnson-laird_analogy_1989,
address = {New York, NY, US},
title = {Analogy and the exercise of creativity},
isbn = {978-0-521-36295-5 978-0-521-38935-8},
abstract = {The main purpose in this chapter is to establish that psychological theories of analogy have so far failed to take the measure of the problem / the processes underlying the discovery of profound analogies are much harder to elucidate than is generally realized / argue that they cannot be guaranteed by any computationally tractable algorithm / I [author] want to try to establish a taxonomy of analogies and to show that there are some forms of analogy that can be retrieved by tractable procedures},
booktitle = {Similarity and analogical reasoning},
publisher = {Cambridge University Press},
author = {Johnson-Laird, Philip N.},
year = {1989},
doi = {10.1017/CBO9780511529863.015},
keywords = {Reasoning, Computer Software, Taxonomies},
pages = {313--331},
file = {Snapshot:files/7290/1989-98813-011.html:text/html},
}
@inproceedings{freksa_strong_2015,
address = {Cham},
series = {Lecture {Notes} in {Computer} {Science}},
title = {Strong {Spatial} {Cognition}},
isbn = {978-3-319-23374-1},
doi = {10.1007/978-3-319-23374-1_4},
abstract = {The ability to perform spatial tasks is crucial for everyday life and of great importance to cognitive agents such as humans, animals, and autonomous robots. Natural embodied and situated agents often solve spatial tasks without detailed knowledge about geometric, topological, or mechanical laws; they directly relate actions to effects enabled by spatio-temporal affordances in their bodies and their environments. Accordingly, we propose a cognitive processing paradigm that makes the spatio-temporal substrate an integral part of the problem-solving engine. We show how spatial and temporal structures in body and environment can support and replace reasoning effort in computational processes: physical manipulation and perception in spatial environments substitute formal computation, in this approach. The strong spatial cognition paradigm employs affordance-based object-level problem solving to complement knowledge-level computation. The paper presents proofs of concept by providing physical spatial solutions to familiar spatial problems for which no equivalent computational solutions are known.},
language = {en},
booktitle = {Spatial {Information} {Theory}},
publisher = {Springer International Publishing},
author = {Freksa, Christian},
editor = {Fabrikant, Sara Irina and Raubal, Martin and Bertolotto, Michela and Davies, Clare and Freundschuh, Scott and Bell, Scott},
year = {2015},
keywords = {Cognitive architecture, Knowledge representation, Pervasive computing, Spatial affordance, Spatial cognition, Ubiquitous computing},
pages = {65--86},
file = {Freksa_2015_Strong_Spatial_Cognition.pdf:files/7291/Freksa_2015_Strong_Spatial_Cognition.pdf:application/pdf},
}
@article{keefer_metaphor_2016,
title = {Metaphor and analogy in everyday problem solving},
volume = {7},
issn = {1939-5086},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/wcs.1407},
doi = {10.1002/wcs.1407},
abstract = {Early accounts of problem solving focused on the ways people represent information directly related to target problems and possible solutions. Subsequent theory and research point to the role of peripheral influences such as heuristics and bodily states. We discuss how metaphor and analogy similarly influence stages of everyday problem solving: Both processes mentally map features of a target problem onto the structure of a relatively more familiar concept. When individuals apply this structure, they use a well-known concept as a framework for reasoning about real world problems and candidate solutions. Early studies found that analogy use helped people gain insight into novel problems. More recent research on metaphor goes further to show that activating mappings has subtle, sometimes surprising effects on judgment and reasoning in everyday problem solving. These findings highlight situations in which mappings can help or hinder efforts to solve problems. WIREs Cogn Sci 2016, 7:394-405. doi: 10.1002/wcs.1407 This article is categorized under: Psychology {\textgreater} Language Psychology {\textgreater} Reasoning and Decision Making},
language = {en},
number = {6},
urldate = {2022-02-06},
journal = {WIREs Cognitive Science},
author = {Keefer, Lucas A. and Landau, Mark J.},
year = {2016},
note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/wcs.1407},
pages = {394--405},
file = {Keefer_Landau_2016_Metaphor_and_analogy_in_everyday_problem_solving.pdf:files/7294/Keefer_Landau_2016_Metaphor_and_analogy_in_everyday_problem_solving.pdf:application/pdf;Snapshot:files/7295/wcs.html:text/html},
}
@inproceedings{mercier_ontology_2022,
title = {Ontology as manifold: towards symbolic and numerical artificial embedding},
shorttitle = {Ontology as manifold},
url = {https://hal.inria.fr/hal-03550354},
language = {en},
urldate = {2022-02-11},
author = {Mercier, Chloé and Alexandre, Frédéric and Viéville, Thierry},
month = jan,
year = {2022},
file = {Snapshot:files/7337/hal-03550354v1.html:text/html},
}
@inproceedings{mercier_creative_2022,
address = {Dunham, UK},
title = {Creative problem solving with tangible artifacts: an overview of computational cognitive frameworks},
abstract = {Creativity and problem solving are two major 21st century skills that are to be addressed in K12 education. In order to better teach these competencies, we need to understand the underlying mechanisms of human cognition. For that purpose, computational neuroscience offers both a theoretical framework and recent experimental results enlightening such cognitive processes. Computational cognitive architectures propose to implement operational algorithms to solve problems. Recent approaches combine problem solving with modular and evolutive knowledge representation, in order to be able to solve ill-defined problems, which are expected to require more creativity. Beyond problem solving, some models also replicate tasks assessing two modes of thinking involved in the creative process, either divergent thinking or convergent thinking, or both. This raises the question of regulation between these dual thinking modes, and beyond, between related strategies of exploration and exploitation. In this contribution, we review some of these approaches and identify what could be useful for a computational cognitive architecture to – virtually – solve a specific problem involving tangible artifacts.
This may contribute to better understand a human learner engaged in this task which could be given in the context of a classroom.},
booktitle = {23rd {International} {Conference} on {Artificial} {Intelligence} in {Education}},
author = {Mercier, Chloé and Vieville, Thierry},
year = {2022},
note = {submitted},
}
@article{mercier_ontology_2022-1,
title = {An ontology to formalize a creative problem solving task},
volume = {Submiteed},
abstract = {We propose to formalize a creative problem solving activity using symbolic knowledge representation in order to better guide the analysis of the observables collected within this activity, and contribute to bridge the gap between learning science, cognitive neuroscience and computational models. The task reviewed here, named {\textbackslash}\#CreaCube, is presented as an open-ended problem which aims to initiate the participants to computational thinking, engaging them to solve a problem appealing to creativity using tangible artifacts. The learner is modeled on the basis of knowledge from learning sciences with the contribution of cognitive neuroscience in the very precise context of this task. We describe in details how we model the activity and the learner engaged in such a task, their behavior as well as their possible mental states. We link the resulting model to some upper cognitive domain ontologies. We show how formalizing these elements using an ontology offers a well-defined specification and the possibility of inferring on the observables, allowing to give a better description of the material states and relate them to the learner mental states. This operationalization of a creative problem-solving activity is part of an exploratory research action, but an effective proof of concept is described in this study.},
journal = {IEEE Transactions on Cognitive and Developmental Systems},
author = {Mercier, Chloé and Romero, Margarida and Alexandre, Frédéric and Vieville, Thierry},
year = {2022},
file = {Mercier_et_al_2022_An_ontology_to_formalize_a_creative_problem_solving_task.pdf:files/7381/Mercier_et_al_2022_An_ontology_to_formalize_a_creative_problem_solving_task.pdf:application/pdf},
}
@article{badre_cognitive_2008,
title = {Cognitive control, hierarchy, and the rostro–caudal organization of the frontal lobes},
volume = {12},
issn = {1364-6613, 1879-307X},
url = {https://www.cell.com/trends/cognitive-sciences/abstract/S1364-6613(08)00061-2},
doi = {10.1016/j.tics.2008.02.004},
language = {English},
number = {5},
urldate = {2022-02-14},
journal = {Trends in Cognitive Sciences},
author = {Badre, David},
month = may,
year = {2008},
pmid = {18403252},
note = {Publisher: Elsevier},
pages = {193--200},
file = {Badre_2008_Cognitive_control,_hierarchy,_and_the_rostro–caudal_organization_of_the_frontal.pdf:files/7587/Badre_2008_Cognitive_control,_hierarchy,_and_the_rostro–caudal_organization_of_the_frontal.pdf:application/pdf;Snapshot:files/7348/S1364-6613(08)00061-2.html:text/html},
}
@article{schlichting_memory_2015,
title = {Memory integration: neural mechanisms and implications for behavior},
volume = {1},
issn = {2352-1546},
shorttitle = {Memory integration},
doi = {10.1016/j.cobeha.2014.07.005},
abstract = {Everyday behaviors require a high degree of flexibility, in which prior knowledge is applied to inform behavior in new situations. Such flexibility is thought to be supported in part by memory integration, a process whereby related memories become interconnected in the brain through recruitment of overlapping neuronal populations. Recent advances in cognitive and behavioral neuroscience highlight the importance of a hippocampal-medial prefrontal circuit in memory integration. Emerging evidence suggests that abstracted representations in medial prefrontal cortex guide reactivation of related memories during new encoding events, thus promoting hippocampal integration of related experiences. Moreover, recent work indicates that integrated memories are called upon during novel situations to facilitate a host of behaviors, from spatial navigation to imagination.},
language = {eng},
journal = {Current Opinion in Behavioral Sciences},
author = {Schlichting, Margaret L. and Preston, Alison R.},
month = feb,
year = {2015},
pmid = {25750931},
pmcid = {PMC4346341},
pages = {1--8},
file = {Schlichting_Preston_2015_Memory_integration.pdf:files/7351/Schlichting_Preston_2015_Memory_integration.pdf:application/pdf},
}
@article{chen_spiral_2021,
title = {The spiral model of collaborative knowledge improvement: an exploratory study of a networked collaborative classroom},
volume = {16},
issn = {1556-1615},
shorttitle = {The spiral model of collaborative knowledge improvement},
url = {https://doi.org/10.1007/s11412-021-09338-6},
doi = {10.1007/s11412-021-09338-6},
abstract = {While there are many studies on students’ collaborative learning at the small group level, pedagogies and strategies for supporting students’ collaborative learning at the class level are underexplored. This study proposes a pedagogical model named the Spiral Model of Collaborative Knowledge Improvement (SMCKI) to inform the design and implementation of multi-layered collaborative learning activities in a networked class where there are many groups of students working collaboratively. Starting with a phase of individual ideation, the pedagogical model scaffolds students to go through five phases of intra-group and inter-group knowledge improvement and refinement, with the goal of supporting the advancement of their individual and collective knowledge. An exploratory case study is presented to illustrate how this model was used in a pre-service teachers’ technology-enhanced learning (TEL) activity design lesson in a Computer-Supported Collaborative Learning (CSCL) environment. The results show that the participants significantly improved the quality of TEL design throughout the five phases of SMCKI. The implications of the findings on designing and implementing CSCL activities in authentic class environments are discussed.},
language = {en},
number = {1},
urldate = {2022-02-15},
journal = {International Journal of Computer-Supported Collaborative Learning},
author = {Chen, Wenli and Tan, Jesmine S. H. and Pi, Zhongling},
month = mar,
year = {2021},
pages = {7--35},
file = {Chen_et_al_2021_The_spiral_model_of_collaborative_knowledge_improvement.pdf:files/7354/Chen_et_al_2021_The_spiral_model_of_collaborative_knowledge_improvement.pdf:application/pdf},
}
@article{law_exploring_2021,
title = {Exploring multilayered collaboration designs},
volume = {16},
issn = {1556-1615},
url = {https://doi.org/10.1007/s11412-021-09342-w},
doi = {10.1007/s11412-021-09342-w},
language = {en},
number = {1},
urldate = {2022-02-15},
journal = {International Journal of Computer-Supported Collaborative Learning},
author = {Law, Nancy and Järvelä, Sanna and Rosé, Carolyn},
month = mar,
year = {2021},
pages = {1--5},
file = {Law_et_al_2021_Exploring_multilayered_collaboration_designs.pdf:files/7355/Law_et_al_2021_Exploring_multilayered_collaboration_designs.pdf:application/pdf},
}
@inproceedings{schatz_architecture_2018,
title = {An {Architecture} {Approach} to {Modeling} the {Remote} {Associates} {Test}},
url = {https://www.semanticscholar.org/paper/An-Architecture-Approach-to-Modeling-the-Remote-Schatz-Laird/7c18c58517a9c4e40117186198b1008b03d291fe},
abstract = {The remote associates test (RAT) depends heavily on memory retrieval and is difficult for humans. A previous model of difficulty on this task accounted for difficulty with a measure incorporating fan and association strength. This paper investigates how the choice of knowledge base and agent strategy impact difficulty on the task while providing a more comprehensive account for human difficulty on this task in terms of cognitive architecture components. The models we created, using the cognitive architecture Soar, vary by using two distinct methods of retrieval from semantic memory. The knowledge bases used in our models vary in that one uses only collocations and compound words to form word associations while the other is from a crowd-sourced dataset with unrestricted types of word association. The model which best matches human difficulty relies on spreading activation to drive retrieval and uses the crowd-sourced dataset for its knowledge base.},
language = {en},
urldate = {2022-02-07},
booktitle = {Proceedings of the 16th international conference on cognitive modelling (iccm).},
author = {Schatz, Jule and Laird, J.},
year = {2018},
pages = {6},
file = {Schatz et al. - An Architecture Approach to Modeling the Remote As.pdf:files/7363/Schatz et al. - An Architecture Approach to Modeling the Remote As.pdf:application/pdf;Snapshot:files/7364/7c18c58517a9c4e40117186198b1008b03d291fe.html:text/html},
}
@article{yadav_computational_2016,
title = {Computational {Thinking} for {All}: {Pedagogical} {Approaches} to {Embedding} 21st {Century} {Problem} {Solving} in {K}-12 {Classrooms}},
volume = {60},
issn = {1559-7075},
shorttitle = {Computational {Thinking} for {All}},
url = {https://doi.org/10.1007/s11528-016-0087-7},
doi = {10.1007/s11528-016-0087-7},
abstract = {The recent focus on computational thinking as a key 21st century skill for all students has led to a number of curriculum initiatives to embed it in K-12 classrooms. In this paper, we discuss the key computational thinking constructs, including algorithms, abstraction, and automation. We further discuss how these ideas are related to current educational reforms, such as Common Core and Next Generation Science Standards and provide specific means that would allow teachers to embed these ideas in their K-12 classrooms, including recommendations for instructional technologists and professional development experts for infusing computational thinking into other subjects. In conclusion, we suggest that computational thinking ideas outlined in this paper are key to moving students from merely being technology-literate to using computational tools to solve problems.},
language = {en},
number = {6},
urldate = {2022-02-07},
journal = {TechTrends},
author = {Yadav, Aman and Hong, Hai and Stephenson, Chris},
month = nov,
year = {2016},
pages = {565--568},
file = {Yadav_et_al_2016_Computational_Thinking_for_All.pdf:files/7365/Yadav_et_al_2016_Computational_Thinking_for_All.pdf:application/pdf},
}
@article{newton_creativity_2014,
title = {Creativity in 21st-century education},
volume = {44},
issn = {1573-9090},
url = {https://doi.org/10.1007/s11125-014-9322-1},
doi = {10.1007/s11125-014-9322-1},
abstract = {The 2006 UNESCO conference Building Creative Competencies for the 21stCentury had international participants and a global reach. The Director-General’s proclamation that “Creativity is our hope” captured the essence of the proceedings and participants saw the focus on creativity as offering solutions to global problems. However, educators tend not to understand creativity appropriately or to value it strongly—and they tend to see it only through Western eyes. Only by considering other cultural views will we gain insights that can inform educational practice in the 21st-century global community. This article discusses some recent studies of creativity, reflecting the growing global interest in it and comparing that interest with established Western perspectives. A more comprehensive, international perspective might support a press for fostering creative thinking in schools and inform practices in our increasingly interconnected world; however, teacher training must introduce teachers to the diversity of views and the expectations of local people.},
language = {en},
number = {4},
urldate = {2022-02-07},
journal = {PROSPECTS},
author = {Newton, Lynn D. and Newton, Douglas P.},
month = dec,
year = {2014},
pages = {575--589},
file = {Newton_Newton_2014_Creativity_in_21st-century_education.pdf:files/7366/Newton_Newton_2014_Creativity_in_21st-century_education.pdf:application/pdf},
}
@article{voogt_comparative_2012,
title = {A comparative analysis of international frameworks for 21st century competences: {Implications} for national curriculum policies},
volume = {44},
issn = {0022-0272},
shorttitle = {A comparative analysis of international frameworks for 21st century competences},
url = {https://doi.org/10.1080/00220272.2012.668938},
doi = {10.1080/00220272.2012.668938},
abstract = {National curricula need to change drastically to comply with the competences needed for the 21st century. In this paper eight frameworks describing 21st century competences were analysed. A comprehensive search for information about 21st century competences was conducted across the official websites of the selected frameworks, resulting in 32 documents that were analysed in detail. Travers and Westbury’s framework of curriculum representations was used to determine horizontal and vertical consistency between the frameworks. The frameworks were compared on their underlying rationales and goals, their definition of 21st century competences, and the recommended strategies for the implementation and assessment of these skills in educational practice. In addition three international studies were examined to analyse how various countries (EU member states, OECD countries) and schools (SITES studies) deal (or not) with 21st century competences. The findings indicate a large extent of alignment between the frameworks about what 21st century competences are and why they are important (horizontal consistency), but intentions and practice seemed still far apart, indicating lack of vertical consistency. The implications of the implementation of 21st century competences in national curriculum policies are discussed and recommendations are provided.},
number = {3},
urldate = {2022-02-07},
journal = {Journal of Curriculum Studies},
author = {Voogt, Joke and Roblin, Natalie Pareja},
month = jun,
year = {2012},
note = {Publisher: Routledge
\_eprint: https://doi.org/10.1080/00220272.2012.668938},
keywords = {curriculum, 21st century competences, assessment., implementation, knowledge society},
pages = {299--321},
file = {Snapshot:files/7367/00220272.2012.html:text/html;Voogt_Roblin_2012_A_comparative_analysis_of_international_frameworks_for_21st_century_competences.pdf:files/7368/Voogt_Roblin_2012_A_comparative_analysis_of_international_frameworks_for_21st_century_competences.pdf:application/pdf},
}
@article{zhang_metacontrol_2020,
title = {Metacontrol of human creativity: {The} neurocognitive mechanisms of convergent and divergent thinking},
volume = {210},
issn = {1053-8119},
shorttitle = {Metacontrol of human creativity},
url = {https://www.sciencedirect.com/science/article/pii/S1053811920300598},
doi = {10.1016/j.neuroimage.2020.116572},
abstract = {Creativity is a complex construct that would benefit from a more comprehensive mechanistic approach. Two processes have been defined to be central to creative cognition: divergent and convergent thinking. These two processes are most often studied using the Alternate Uses Test (heavily relying on divergent thinking), and the Remote Associates Test (heavily relying on convergent thinking, at least with analytical solutions). Although creative acts should be regarded compound processes, most behavioral and neuroimaging studies ignore the composition of basic operations relevant for the task they investigate. In order to provide leverage for a more mechanistic, and eventually even comprehensive computational, approach to creative cognition, we compare findings from divergent and convergent thinking studies and review the similarities and differences between the two underlying types of processes, from a neurocognitive perspective with a strong focus on cortical structures. In this narrative review, we discuss a broad scope of neural correlates of divergent and convergent thinking. We provide a first step towards theoretical integration, by suggesting that creative cognition in divergent- and convergent-thinking heavy tasks is modulated by metacontrol states, where divergent thinking and insight solutions in convergent-thinking tasks seem to benefit from metacontrol biases towards flexibility, whereas convergent, analytical thinking seems to benefit from metacontrol biases towards persistence. These particular biases seem to be reflected by specific cortical brain-activation patterns, involving left frontal and right temporal/parietal networks. Our tentative framework could serve as a first proxy to guide neuroscientific creativity research into assessing more mechanistic details of human creative cognition.},
language = {en},
urldate = {2022-02-07},
journal = {NeuroImage},
author = {Zhang, Weitao and Sjoerds, Zsuzsika and Hommel, Bernhard},
month = apr,
year = {2020},
pages = {116572},
file = {ScienceDirect Snapshot:files/7369/S1053811920300598.html:text/html;Zhang_et_al_2020_Metacontrol_of_human_creativity.pdf:files/7370/Zhang_et_al_2020_Metacontrol_of_human_creativity.pdf:application/pdf},
}
@article{mednick_remote_1968,
title = {The {Remote} {Associates} {Test}*},
volume = {2},
issn = {2162-6057},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/j.2162-6057.1968.tb00104.x},
doi = {10.1002/j.2162-6057.1968.tb00104.x},
language = {en},
number = {3},
urldate = {2022-02-06},
journal = {The Journal of Creative Behavior},
author = {Mednick, Sarnoff A.},
year = {1968},
note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/j.2162-6057.1968.tb00104.x},
pages = {213--214},
file = {Snapshot:files/7371/j.2162-6057.1968.tb00104.html:text/html},
}
@incollection{romero_techno-creative_2022,
title = {Techno-creative problem solving ({TCPS}) framework for transversal epistemological and didactical positions: the cases of {CreaCube} and the {Tower} of {Hanoi} task},
shorttitle = {Techno-creative problem solving ({TCPS}) framework for transversal epistemological and didactical positions},
abstract = {The interdisciplinary nature of STEM education is a fertile ground for the development of transversal competencies. The study of STEM activities requires not only to consider domain-specific knowledge and skills, but also to possess several transversal competences, among them problem solving, creativity and computational thinking to fully benefit from the learning process initiated by these activities. Considering these transversal competencies separately leads to several points of tensions, from a more integrative, holistic point of view. Hence, it is necessary to look at these aspects from a more transdisciplinary position, eventually overcoming limits of disciplinary-orientated approaches thus linking the existing theoretical frameworks and pedagogical practices. In this article we describe how the techno-creative problem-solving framework (TCPS) could enrich the analysis of STEM teaching and learning from a transversal epistemological and didactical position. In order to investigate the transdisciplinary potential of TCPS, we provide the analysis of two problem-solving tasks, Tower of Hanoi and CreaCube. The analysis of these tasks through the TCPS raises the existing tensions on how problem solving, creativity and computational thinking are considered in different domains to highlight commonalities and differences between different approaches and to deepen the discussion about their possible connections.},
author = {Romero, Margarida and Freiman, V and Rafalska, Maryna},
month = jan,
year = {2022},
file = {Romero_et_al_2022_Techno-creative_problem_solving_(TCPS)_framework_for_transversal.pdf:files/7375/Romero_et_al_2022_Techno-creative_problem_solving_(TCPS)_framework_for_transversal.pdf:application/pdf},
}
@techreport{clairis_value_2021,
title = {Value, confidence and deliberation: a functional partition of the medial prefrontal cortex across preference tasks},
copyright = {© 2021, Posted by Cold Spring Harbor Laboratory. This pre-print is available under a Creative Commons License (Attribution-NonCommercial-NoDerivs 4.0 International), CC BY-NC-ND 4.0, as described at http://creativecommons.org/licenses/by-nc-nd/4.0/},
shorttitle = {Value, confidence and deliberation},
url = {https://www.biorxiv.org/content/10.1101/2020.09.17.301291v2},
abstract = {Deciding about courses of action involves minimizing costs and maximizing benefits. Decision neuroscience studies have suggested a dissociation between the ventral and dorsal medial prefrontal cortex (vmPFC and dmPFC), which would provide estimates of goal value and action cost, respectively. However, this general idea of opponent reward and effort systems has been challenged by several studies that suggested alternative functional dissociations. These contradictions might reflect the diversity of tasks used to investigate the reward/effort tradeoff, and/or the confusion with a metacognitive tradeoff that minimizes the duration of deliberation while maximizing confidence in the behavioral response. Here, we used an original approach with the goal of identifying consistencies across several preference tasks, from likeability ratings to binary decisions involving both attribute integration and option comparison. FMRI results confirmed the vmPFC as a generic valuation system, its activity increasing with reward value and decreasing with effort cost. In contrast, more dorsal regions were not concerned with attributes of options but with metacognitive estimates, confidence level being computed in the mPFC and deliberation time in the dmPFC. Thus, assessing commonalities across preference tasks might help reaching a unified view of the neural mechanisms underlying the cost/benefit tradeoffs that drive human behavior.},
language = {en},
urldate = {2022-02-24},
institution = {bioRxiv},
author = {Clairis, N. and Pessiglione, M.},
month = jul,
year = {2021},
doi = {10.1101/2020.09.17.301291},
note = {Section: New Results
Type: article},
pages = {2020.09.17.301291},
file = {Clairis_Pessiglione_2021_Value,_confidence_and_deliberation.pdf:files/7379/Clairis_Pessiglione_2021_Value,_confidence_and_deliberation.pdf:application/pdf;Snapshot:files/7380/2020.09.17.html:text/html},
}
@article{eppe_intelligent_2022,
title = {Intelligent problem-solving as integrated hierarchical reinforcement learning},
volume = {4},
copyright = {2022 Springer Nature Limited},
issn = {2522-5839},
url = {https://www.nature.com/articles/s42256-021-00433-9},
doi = {10.1038/s42256-021-00433-9},
abstract = {According to cognitive psychology and related disciplines, the development of complex problem-solving behaviour in biological agents depends on hierarchical cognitive mechanisms. Hierarchical reinforcement learning is a promising computational approach that may eventually yield comparable problem-solving behaviour in artificial agents and robots. However, so far, the problem-solving abilities of many human and non-human animals are clearly superior to those of artificial systems. Here we propose steps to integrate biologically inspired hierarchical mechanisms to enable advanced problem-solving skills in artificial agents. We first review the literature in cognitive psychology to highlight the importance of compositional abstraction and predictive processing. Then we relate the gained insights with contemporary hierarchical reinforcement learning methods. Interestingly, our results suggest that all identified cognitive mechanisms have been implemented individually in isolated computational architectures, raising the question of why there exists no single unifying architecture that integrates them. As our final contribution, we address this question by providing an integrative perspective on the computational challenges to develop such a unifying architecture. We expect our results to guide the development of more sophisticated cognitively inspired hierarchical machine learning architectures.},
language = {en},
number = {1},
urldate = {2022-03-09},
journal = {Nature Machine Intelligence},
author = {Eppe, Manfred and Gumbsch, Christian and Kerzel, Matthias and Nguyen, Phuong D. H. and Butz, Martin V. and Wermter, Stefan},
month = jan,
year = {2022},
note = {Number: 1
Publisher: Nature Publishing Group},
keywords = {Computer science, Cognitive control, Problem solving, Computational models, Learning algorithms},
pages = {11--20},
file = {Snapshot:files/7383/s42256-021-00433-9.html:text/html},
}
@article{stanovich_individual_2000,
title = {Individual {Differences} in {Reasoning}: {Implications} for the {Rationality} {Debate}},
volume = {23},
shorttitle = {Individual {Differences} in {Reasoning}},
doi = {10.1017/S0140525X00003435},
abstract = {Much research in the last two decades has demonstrated that human responses deviate from the performance deemed normative according to various models of decision making and rational judgment (e.g., the basic axioms of utility theory). This gap between the normative and the descriptive can be interpreted as indicating systematic irrationalities in human cognition. However, four alternative interpretations preserve the assumption that human behavior and cognition is largely rational. These posit that the gap is due to (1) performance errors, (2) computational limitations, (3) the wrong norm being applied by the experimenter, and (4) a different construal of the task by the subject. In the debates about the viability of these alternative explanations, attention has been focused too narrowly on the model response. In a series of experiments involving most of the classic tasks in the heuristics and biases literature, we have examined the implications of individual differences in performance for each of the four explanations of the normative/descriptive gap. Performance errors are a minor factor in the gap; computational limitations underlie non-normative responding on several tasks, particularly those that involve some type of cognitive decontextualization. Unexpected patterns of covariance can suggest when the wrong norm is being applied to a task or when an alternative construal of the task should be considered appropriate.},
journal = {The Behavioral and brain sciences},
author = {Stanovich, Keith and West, Richard},
month = nov,
year = {2000},
pages = {645--65; discussion 665},
file = {Full Text PDF:files/7385/Stanovich and West - 2000 - Individual Differences in Reasoning Implications .pdf:application/pdf},
}
@article{quillien_roles_2019,
title = {The {Roles} of {Convergent}, {Divergent} {Thinking}, and {Contextual} {Focus} during {Scientific} {Reasoning}: {Birth} of the “{Z}” {Model}},
shorttitle = {The {Roles} of {Convergent}, {Divergent} {Thinking}, and {Contextual} {Focus} during {Scientific} {Reasoning}},
url = {http://conservancy.umn.edu/handle/11299/217149},
abstract = {The aim of this paper is to bridge the process of scientific reasoning with the field of cognitive science, and more specifically, the cognitive mechanisms involved during reasoning. This intent of bridging scientific reasoning with cognitive mechanisms gave birth to a new model: the “Z” model of scientific reasoning. This model integrates the traditional scientific reasoning steps while depicting the cognitive mechanisms and mental flexibilities at use during reasoning. The goal of this experiment was to test the “Z” model and thus investigate the role of divergent and convergent thinking during scientific reasoning. In addition, the “Z” model highlights the importance of Contextual Focus during scientific reasoning. Contextual Focus is defined as the cognitive shift between modes of thoughts. Contextual Focus was tested to investigate its predictive power on our specific measure of scientific reasoning (Bouncing Ball Reasoning Task; BBRT) and a broader measure of scientific reasoning (Lawson Test of Scientific Reasoning; LTSR). In addition, the predictive power over scientific reasoning performances of Intellect and Openness, the personality traits of interest, was also tested. First, we hypothesized that participants experimentally primed to think divergently should perform better during the exploration of the problem space during a scientific reasoning task (Phase 1 of BBRT). As predicted, participants in the divergent thinking group generated on average more hypotheses than the participants in the convergent thinking and the control groups. Secondly, we hypothesized that participants experimentally primed to think convergently should perform better during the exploitation of the evaluative space during a scientific reasoning task (Phase 2 of BBRT). As predicted, participants in the convergent thinking group displayed on average fewer categorical errors than the participants in the divergent thinking or the control groups. In addition, Contextual Focus was found to be a significant predictor of the overall performance in exploring the problem space of our specific scientific reasoning problem. Intellect score over broader scientific reasoning (LTSR) performance, Contextual Focus and Intellect were found to be significant predictors of broader scientific reasoning (LTSR) performance. Those findings can also be interpreted with broader cognitive science lenses. Given that complex mental tasks such as problem solving and critical thinking also require divergent and convergent thinking, future research should test whether the priming used during our experimental protocol also leads to an advantage on more general reasoning tasks.},
language = {en},
urldate = {2022-03-14},
author = {Quillien, Jean-Baptiste},
month = sep,
year = {2019},
note = {Accepted: 2020-11-17T13:56:35Z},
file = {Quillien_2019_The Roles of Convergent, Divergent Thinking, and Contextual Focus during.pdf:files/7390/Quillien_2019_The Roles of Convergent, Divergent Thinking, and Contextual Focus during.pdf:application/pdf;Snapshot:files/7391/217149.html:text/html},
}
@article{mednick_associative_1962,
title = {The associative basis of the creative process.},
doi = {10.1037/H0048850},
abstract = {An associative interpretation of the process of creative thinking is presented and three ways in which creative solutions may be achieved are indicated—serendipity, similarity, and mediation. The intent of this paper is the presentation of an associative interpretation of the process of creative thinking. The explanation is not directed to any specific field of application such as art or science but attempts to delineate processes that underlie all creative thought. The discussion will take the following form, (a) First, we will define creative thinking in associative terms and indicate three ways in which creative solutions may be achieved—serendipity, similarity, and mediation, (b) This definition will allow us to deduce those individual difference variables which will facilitate creative performance, (c) Consideration of the definition of the creative process has suggested an operational statement of the definition in the form of a test. The test will be briefly described along with some preliminary research results. (d) The paper will conclude with a discussion of predictions regarding the influence of certain experimentally manipulable variables upon the creative process. Creative individuals and the processes by which they manifest their creativity have excited a good deal of},
journal = {Psychological review},
author = {Mednick, S.},
year = {1962},
file = {Mednick_1962_The_associative_basis_of_the_creative_process.pdf:files/7402/Mednick_1962_The_associative_basis_of_the_creative_process.pdf:application/pdf},
}
@misc{noauthor_associative_nodate,
title = {The associative basis of the creative process. - {PsycNET}},
url = {https://content.apa.org/record/1963-06161-001},
abstract = {An associative theory of creative thinking has been outlined. Differences between high creatives and low creatives have been predicted along specified dimensions. Predictions have been made regarding the effect on the creative process of some experimentally manipulable variables. The associative definition of the creative process has taken the operational form of a test. Some preliminary research with this test is described. (PsycINFO Database Record (c) 2016 APA, all rights reserved)},
language = {en},
urldate = {2022-03-14},
journal = {APA PsycNET},
doi = {10.1037/h0048850},
file = {Full Text:files/7405/The associative basis of the creative process. - P.pdf:application/pdf;Snapshot:files/7406/1963-06161-001.html:text/html},
}
@article{levy_root_2012,
title = {The root of all value: a neural common currency for choice},
volume = {22},
issn = {0959-4388},
shorttitle = {The root of all value},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4093837/},
doi = {10.1016/j.conb.2012.06.001},
abstract = {How do humans make choices between different types of rewards? Economists have long argued on theoretical grounds that humans typically make these choices as if the values of the options they consider have been mapped to a single common scale for comparison. Neuroimaging studies in humans have recently begun to suggest the existence of a small group of specific brain sites that appear to encode the subjective values of different types of rewards on a neural common scale, almost exactly as predicted by theory. We have conducted a meta analysis using data from thirteen different functional magnetic resonance imaging studies published in recent years and we show that the principle brain area associated with this common representation is a subregion of the ventromedial prefrontal cortex (vmPFC)/orbitofrontal cortex (OFC). The data available today suggest that this common valuation path is a core system that participates in day-to-day decision making suggesting both a neurobiological foundation for standard economic theory and a tool for measuring preferences neurobiologically. Perhaps even more exciting is the possibility that our emerging understanding of the neural mechanisms for valuation and choice may provide fundamental insights into pathological choice behaviors like addiction, obesity and gambling.},
number = {6},
urldate = {2022-03-15},
journal = {Current opinion in neurobiology},
author = {Levy, Dino J and Glimcher, Paul W},
month = dec,
year = {2012},
pmid = {22766486},
pmcid = {PMC4093837},
pages = {1027--1038},
file = {Levy_Glimcher_2012_The root of all value.pdf:files/7409/Levy_Glimcher_2012_The root of all value.pdf:application/pdf},
}
@article{wiggins_searching_2006,
title = {Searching for computational creativity},
volume = {24},
issn = {1882-7055},
url = {https://doi.org/10.1007/BF03037332},
doi = {10.1007/BF03037332},
abstract = {Boden’s1,2) philosophical account of creativity has been criticised on the grounds that it does not properly capture some aspects of creative situations.5) Wiggins13) has presented a formalisation of Boden’s account, which allows such issues to be examined more precisely. We explore the relationship between traditional AI search methods and Boden’s abstraction of creative behaviour, and revisit Bundy’s argument in the context of that exploration.},
language = {en},
number = {3},
urldate = {2022-03-15},
journal = {New Generation Computing},
author = {Wiggins, Geraint A.},
month = sep,
year = {2006},
pages = {209--222},
file = {Wiggins_2006_Searching for computational creativity.pdf:files/7411/Wiggins_2006_Searching for computational creativity.pdf:application/pdf},
}
@article{ni_how_2014,
title = {How to {Improve} {Divergent} {Thinking} {Capability} by {Information} {Technology} and {Extenics}},
volume = {31},
doi = {10.1016/j.procs.2014.05.256},
abstract = {Divergent Thinking capability has become increasingly important for innovation and problem solving. We need efficient and effective ways to support the divergent thinking process. Based on Basic-element theory of Extenics, a new model to improve the divergent thinking capability has been developed using information management and extension transformation. With the guide of the extension innovation method, we collect attributes of different things through information technology on the web, and then extend many divergent thinking directions systematically. The case study shows it is helpful as a common innovative approach to improve divergent thinking capability by integration of information technology and Extenics.},
journal = {Procedia Computer Science},
author = {Ni, Mengjing and Yang, Li and Chen, Jinzi and Chen, Hong and Li, Xingsen},
month = dec,
year = {2014},
pages = {158--164},
file = {Ni_et_al_2014_How_to_Improve_Divergent_Thinking_Capability_by_Information_Technology_and.pdf:files/7450/Ni_et_al_2014_How_to_Improve_Divergent_Thinking_Capability_by_Information_Technology_and.pdf:application/pdf},
}
@article{vieville_implementing_2001,
title = {Implementing a multi-model estimation method},
url = {https://hal.inria.fr/inria-00000172},
abstract = {This work is realized within the scope of a general attempt to understand parametric adaptation, regarding visual perception. The key idea is to analyze how we may use multi-model parametric estimation as a 1st step towards categorization. More generally, the goal is to formalize how the notion of ``objects'' or ``events'' in an application may be reduced to a choice in a hierarchy of parametric models used to estimate the underlying data categorization. These mechanisms are to be linked with what occurs in the cerebral cortex where object recognition corresponds to a parametric neuronal estimation (see for instanced Page 2000 for a discussion and Freedman et al 2001 for an example regarding the primate visual cortex). We thus hope to bring here an algorithmic element in relation with the ``grand-ma'' neuron modelization. We thus revisit the problem of parameter estimation in computer vision, presented here as a simple optimization problem, considering (i) non-linear implicit measurement equations and parameter constraints, plus (ii) robust estimation in the presence of outliers and (iii) multi-model comparisons. Here, (1) a projection algorithm based on generalizations of square-root decompositions allows an efficient and numerically stable local resolution of a set of non-linear equations. On the other hand, (2) a robust estimation module of a hierarchy of non-linear models has been designed and validated. A step ahead, the software architecture of the estimation module is discussed with the goal of being integrated in reactive software environments or within applications with time constraints.},
language = {en},
urldate = {2022-03-18},
journal = {International Journal of Computer Vision},
author = {Viéville, Thierry and Lingrand, Diane and Gaspard, François},
month = oct,
year = {2001},
file = {Snapshot:files/7454/inria-00000172.html:text/html;Viéville et al_2001_Implementing a multi-model estimation method.pdf:files/6863/Viéville et al_2001_Implementing a multi-model estimation method.pdf:application/pdf;Viéville et al_2001_Implementing a multi-model estimation method.pdf:files/7453/Viéville et al_2001_Implementing a multi-model estimation method.pdf:application/pdf},
}
@incollection{laird_soargeneral_1986,
address = {Boston, MA},
series = {The {Kluwer} {International} {Series} in {Engineering} and {Computer} {Science}},
title = {Soar—{A} {General} {Problem}-{Solving} {Architecture}},
isbn = {978-1-4613-2277-1},
url = {https://doi.org/10.1007/978-1-4613-2277-1_15},
abstract = {Soar is a problem solving system that is based on formulating all activity (both problems and routine tasks) as heuristic search in problem spaces. A problem space consists of a set of states and a set of operators that transform one state into another. Starting from an initial state the problem solver applies a sequence of operators in an attempt to reach a desired state. Soar uses a production system1 to implement elementary operators, tests for goal satisfaction and failure, and search control — information relevant to the selection of goals, problem spaces, states, and operators. It is possible to use a problem space that has no search control, only operators and goal recognizers. Such a space will work correctly, but will be slow because of the amount of search required.},
language = {en},
urldate = {2022-03-19},
booktitle = {Universal {Subgoaling} and {Chunking}: {The} {Automatic} {Generation} and {Learning} of {Goal} {Hierarchies}},
publisher = {Springer US},
author = {Laird, John and Rosenbloom, Paul and Newell, Allen},
editor = {Laird, John and Rosenbloom, Paul and Newell, Allen},
year = {1986},
doi = {10.1007/978-1-4613-2277-1_15},
pages = {286--288},
file = {Laird et al_1986_Soar—A General Problem-Solving Architecture.pdf:files/7456/Laird et al_1986_Soar—A General Problem-Solving Architecture.pdf:application/pdf},
}
@article{arnett_adolescence_2001,
title = {Adolescence and emerging adulthood: {A} cultural approach (2nd ed.).},
shorttitle = {Adolescence and emerging adulthood},
doi = {10.1093/acprof:oso/9780195309379.001.0001},
abstract = {The author's goal of presenting a fresh conception of young people's development has resulted in chapters on topics not as strongly represented in most other textbooks. Most textbooks have a discussion of moral development, but this textbook has a chapter on cultural beliefs, including moral development, religious beliefs, political beliefs, and a discussion of individualistic and collectivistic beliefs in various cultures. The chapter on cultural beliefs provides a good basis for a cultural understanding of adolescent development, because it emphasizes how the judgments we make about how adolescents should think and act are almost always rooted in beliefs we have learned in the course of growing up in a particular culture. In this textbook there is a chapter on gender that focuses on cultural variations and historical changes in gender roles, in addition to discussions of gender issues in other chapters This textbook also has an entire chapter on work, which is central to the lives of adolescents in developing countries because a high proportion of them are not in school. Each chapter contains a number of critical thinking questions the purpose of which is to inspire students to a higher level of analysis and reflection about the ideas and information in the chapters--higher, that is, than they would be likely to achieve simply by reading the chapter. (PsycINFO Database Record (c) 2012 APA, all rights reserved)},
author = {Arnett, Jeffrey},
month = jan,
year = {2001},
}
@article{purves_interplay_2001,
title = {The {Interplay} of {Emotion} and {Reason}},
url = {https://www.ncbi.nlm.nih.gov/books/NBK10822/},
abstract = {The experience of emotion—even on a subconscious level—has a powerful influence on the neural faculties responsible for making rational decisions. Evidence for this statement has come principally from studies of patients with damage to parts of the orbital and medial prefrontal cortex, as well as patients with injury or disease involving the amygdala (see Box D). Such patients have in common an impairment in emotional processing, especially emotions engendered by complex personal and social situations, and an inability to make advantageous decisions (see also Chapter 26).},
language = {en},
urldate = {2022-03-22},
journal = {Neuroscience. 2nd edition},
author = {Purves, Dale and Augustine, George J. and Fitzpatrick, David and Katz, Lawrence C. and LaMantia, Anthony-Samuel and McNamara, James O. and Williams, S. Mark},
year = {2001},
note = {Publisher: Sinauer Associates},
file = {Snapshot:files/7463/NBK10822.html:text/html},
}
@article{fikes_role_1985,
title = {The role of frame-based representation in reasoning},
volume = {28},
issn = {0001-0782},
url = {https://doi.org/10.1145/4284.4285},
doi = {10.1145/4284.4285},
abstract = {A frame-based representation facility contributes to a knowledge system's ability to reason and can assist the system designer in determining strategies for controlling the system's reasoning.},
number = {9},
urldate = {2022-03-23},
journal = {Communications of the ACM},
author = {Fikes, Richard and Kehler, Tom},
month = sep,
year = {1985},
pages = {904--920},
file = {Fikes_Kehler_1985_The_role_of_frame-based_representation_in_reasoning.pdf:files/7465/Fikes_Kehler_1985_The_role_of_frame-based_representation_in_reasoning.pdf:application/pdf},
}
@article{cessac_dynamics_2008,
title = {On {Dynamics} of {Integrate}-and-{Fire} {Neural} {Networks} with {Adaptive} {Conductances}},
volume = {2},
url = {https://hal.inria.fr/inria-00338369},
abstract = {We present a mathematical analysis of a networks with Integrate-and-Fire neurons with conductance based synapses. Taking into account the realistic fact that the spike time is only known within some finite precision, we propose a model where spikes are effective at times multiple of a characteristic time scale, which can be arbitrary small (in particular, well beyond the numerical precision). We make a complete mathematical characterization of the model-dynamics and obtain the following results. The asymptotic dynamics is composed by finitely many stable periodic orbits, whose number and period can be arbitrary large and can diverge in a region of the synaptic weights space, traditionally called the ``edge of chaos'', a notion mathematically well defined in the present paper. Furthermore, except at the edge of chaos, there is a one-to-one correspondence between the membrane potential trajectories and the raster plot. This shows that the neural code is entirely ``in the spikes'' in this case. As a key tool, we introduce an order parameter, easy to compute numerically, and closely related to a natural notion of entropy, providing a relevant characterization of the computational capabilities of the network. This allows us to compare the computational capabilities of leaky and Integrate-and-Fire models and conductance based models. The present study considers networks with constant input, and without time-dependent plasticity, but the framework has been designed for both extensions.},
language = {en},
number = {2},
urldate = {2022-03-23},
journal = {Frontiers in Neuroscience},
author = {Cessac, Bruno and Viéville, Thierry},
year = {2008},
file = {Snapshot:files/7467/inria-00338369.html:text/html},
}
@article{boden_creativity_2007,
title = {Creativity in a nutshell},
volume = {5},
issn = {1755-1196, 1477-1756},
url = {https://www.cambridge.org/core/journals/think/article/creativity-in-a-nutshell/E74A8FA0906C3AA5A1813FFBD56860F9},
doi = {10.1017/S147717560000230X},
abstract = {Clarifying what creativity is the first step towards answering the question: could a computer be creative?},
language = {en},
number = {15},
urldate = {2022-03-28},
journal = {Think},
author = {Boden, Margaret A.},
year = {2007},
note = {Publisher: Cambridge University Press},
pages = {83--96},
file = {Boden_2007_Creativity_in_a_nutshell.pdf:files/7125/Boden_2007_Creativity_in_a_nutshell.pdf:application/pdf;Snapshot:files/7471/E74A8FA0906C3AA5A1813FFBD56860F9.html:text/html},
}
@article{hommel_towards_2017,
title = {Towards a {Unitary} {Approach} to {Human} {Action} {Control}},
volume = {21},
issn = {1364-6613},
url = {https://www.sciencedirect.com/science/article/pii/S1364661317301973},
doi = {10.1016/j.tics.2017.09.009},
abstract = {From its academic beginnings the theory of human action control has distinguished between endogenously driven, intentional action and exogenously driven, habitual, or automatic action. We challenge this dual-route model and argue that attempts to provide clear-cut and straightforward criteria to distinguish between intentional and automatic action have systematically failed. Specifically, we show that there is no evidence for intention-independent action, and that attempts to use the criterion of reward sensitivity and rationality to differentiate between intentional and automatic action are conceptually unsound. As a more parsimonious, and more feasible, alternative we suggest a unitary approach to action control, according to which actions are (i) represented by codes of their perceptual effects, (ii) selected by matching intention-sensitive selection criteria, and (ii) moderated by metacontrol states.},
language = {en},
number = {12},
urldate = {2022-03-24},
journal = {Trends in Cognitive Sciences},
author = {Hommel, Bernhard and Wiers, Reinout W.},
month = dec,
year = {2017},
keywords = {intention, cognitive control, automaticity, dual-route model, executive functions, metacontrol},
pages = {940--949},
file = {ScienceDirect Snapshot:files/7472/S1364661317301973.html:text/html},
}
@article{baevski_data2vec_2022,
title = {data2vec: {A} {General} {Framework} for {Self}-supervised {Learning} in {Speech}, {Vision} and {Language}},
shorttitle = {data2vec},
url = {http://arxiv.org/abs/2202.03555},
abstract = {While the general idea of self-supervised learning is identical across modalities, the actual algorithms and objectives differ widely because they were developed with a single modality in mind. To get us closer to general self-supervised learning, we present data2vec, a framework that uses the same learning method for either speech, NLP or computer vision. The core idea is to predict latent representations of the full input data based on a masked view of the input in a self-distillation setup using a standard Transformer architecture. Instead of predicting modality-specific targets such as words, visual tokens or units of human speech which are local in nature, data2vec predicts contextualized latent representations that contain information from the entire input. Experiments on the major benchmarks of speech recognition, image classification, and natural language understanding demonstrate a new state of the art or competitive performance to predominant approaches.},
urldate = {2022-03-31},
journal = {arXiv:2202.03555 [cs]},
author = {Baevski, Alexei and Hsu, Wei-Ning and Xu, Qiantong and Babu, Arun and Gu, Jiatao and Auli, Michael},
month = feb,
year = {2022},
note = {arXiv: 2202.03555},
keywords = {Computer Science - Machine Learning},
file = {arXiv.org Snapshot:files/7477/2202.html:text/html;Baevski_et_al_2022_data2vec.pdf:files/7478/Baevski_et_al_2022_data2vec.pdf:application/pdf},
}
@article{gris_assessment_2021,
title = {Assessment {Measures} in {Game}-based {Learning} {Research}: {A} {Systematic} {Review}},
volume = {8},
shorttitle = {Assessment {Measures} in {Game}-based {Learning} {Research}},
doi = {10.17083/ijsg.v8i1.383},
abstract = {The use of games in educational contexts is well documented in GBL research. Nevertheless, effectiveness evidence needs to be more extensively analyzed. An effective GBL strategy should address the learning aspects and promote players' engagement in an easy-to-use system. To gather the information already present in literature, we sought to answer how learning, engagement, and usability of games are evaluated in GBL research. We conducted a systematic review of empirical studies in ERIC, IEEE, Springer, and Web of Science databases. We included 91 studies for the final analysis and categorized their measures and instruments. We find a prevalence of learning assessments over engagement and usability assessments. Learning is mainly evaluated by direct measures, while indirect measures mostly assess engagement and usability. The use of indirect measures and instruments without psychometric qualities compromises the strength of the evidence for the effectiveness of game-based learning. Future studies should add direct assessments and indirect measures with psychometric qualities to assess engagement and usability. The study's limitations are discussed.},
journal = {International Journal of Serious Games},
author = {Gris, Gabriele and Bengtson, Clarissa},
month = mar,
year = {2021},
pages = {3--26},
file = {Gris_Bengtson_2021_Assessment_Measures_in_Game-based_Learning_Research.pdf:files/7480/Gris_Bengtson_2021_Assessment_Measures_in_Game-based_Learning_Research.pdf:application/pdf},
}
@article{rougier_implicit_2009,
title = {Implicit and {Explicit} {Representations}},
volume = {22},
url = {https://hal.inria.fr/inria-00336167},
doi = {10.1016/j.neunet.2009.01.00},
abstract = {During the past decades, the symbol grounding problem, as it has been identified by Harnard, became a prominent problem in the cognitive science society. The idea that a symbol was much more than a mere meaningless token that can be processed through some algorithm, sheds a new light on higher brain functions such as language and cognition. We present in this article a computational framework that may help our understanding of the nature of grounded representations. Two models are briefly introduced that aim at emphasizing the difference we make between implicit and explicit representations.},
number = {2},
urldate = {2022-04-02},
journal = {Neural Networks},
author = {Rougier, Nicolas P.},
year = {2009},
note = {Publisher: Elsevier},
keywords = {Neuroscience, Cognition, Computational, Embodied, Representation, Symbol},
pages = {155--160},
}
@article{nijstad_dual_2010,
title = {The {Dual} {Pathway} to {Creativity} {Model}: {Creative} {Ideation} as a {Function} of {Flexibility} and {Persistence}},
volume = {21},
shorttitle = {The {Dual} {Pathway} to {Creativity} {Model}},
doi = {10.1080/10463281003765323},
abstract = {The dual pathway to creativity model argues that creativity—the generation of original and appropriate ideas—is a function of cognitive flexibility and cognitive persistence, and that dispositional or situational variables may influence creativity either through their effects on flexibility, on persistence, or both. This model is tested in a number of studies in which participants performed creative ideation tasks. We review work showing that cognitive flexibility, operationalised as the number of content categories surveyed, directly relates to idea originality, but that originality can also be achieved by exploring a few content categories in great depth (i.e., persistence). We also show that a global processing mode is associated with cognitive flexibility, but only leads to high originality in tasks that capitalise on cognitive flexibility. We finally show that activating positive mood states enhance creativity because they stimulate flexibility, while activating negative mood states can enhance creativity because they stimulate persistence. Implications for theory and practice are discussed.},
journal = {European Review of Social Psychology},
author = {Nijstad, Bernard and De Dreu, Carsten and Rietzschel, Eric and Baas, Matthijs},
month = mar,
year = {2010},
pages = {34--77},
}
@book{herbert_pedagogy_2010,
address = {London},
title = {The {Pedagogy} of {Creativity}},
isbn = {978-0-203-85546-1},
abstract = {The Pedagogy of Creativity represents a groundbreaking study linking the pedagogy of classroom creativity with psychoanalytical theories. Taking a classroom-based example of poststructuralist methodology as its starting point, Anna Herbert’s investigation explores the relationship between creativity seen in psychological activity, such as dreams, and creativity seen in the classroom, asking the following questions:
What might a methodology which taps into different forms of creativity look like?
Could such a methodology support current neuropsychological theories of memory and learning?
What are the consequences of imaginary and symbolic orders of knowledge for the understanding of both conscious and unconscious creativity in the classroom?
Exploring the ideas of a number of psychological analysts including Jacques Lacan’s four discourses, concepts of ‘the other’ and the theories of Postructuralist thinkers including Levinas, Mead and Kristeva, Herbert explains how different theories can be used to develop creativity in the classroom and surmount obstacles preventing creative environments.
Clearly presenting both theoretical positions and their bearing on classroom practice, teachers at all levels will benefit from this innovative approach to creativity, as will school psychologists and all professionals interested in the links between psychoanalysis and pedagogy.
Herbert clearly communicates both theoretical positions and their bearing on classroom practice. Teacher at all levels will benefit from this innovative approach to creativity, as will school psychologists and other professionals interested in the links between psychoanalysis and pedagogy.},
publisher = {Routledge},
author = {Herbert, Anna},
month = feb,
year = {2010},
doi = {10.4324/9780203855461},
}
@article{berthier_les_2019,
title = {Les neurosciences et l’avenir de l’éducation},
volume = {428},
issn = {0337-307X},
url = {https://www.cairn.info/revue-futuribles-2019-1-page-81.htm},
abstract = {Compl\&\#233;tant la s\&\#233;rie sur le cerveau ouverte dans ce num\&\#233;ro de Futuribles, cet article de Jean-Luc Berthier montre concr\&\#232;tement comment les neurosciences peuvent faire \&\#233;voluer les m\&\#233;thodes \&\#233;ducatives. S\&\#8217;appuyant sur un certain nombre d\&\#8217;exp\&\#233;rimentations lanc\&\#233;es en France, en particulier dans le cadre des \&\#171;\&\#160;cogni\&\#8217;classes\&\#160;\&\#187;, l\&\#8217;auteur montre ici comment la recherche en neurosciences, en permettant de mieux comprendre les fonctionnalit\&\#233;s du cerveau, offre de nouvelles voies d\&\#8217;apprentissage aux enseignants et \&\#224; leurs \&\#233;l\&\#232;ves.Jean-Luc Berthier pr\&\#233;sente ainsi toute une s\&\#233;rie de nouvelles modalit\&\#233;s \&\#233;ducatives visant \&\#224; faciliter la m\&\#233;morisation, \&\#224; mieux capter l\&\#8217;attention, \&\#224; diff\&\#233;rencier les pratiques selon le profil de l\&\#8217;\&\#233;l\&\#232;ve, etc. Il d\&\#233;crit \&\#233;galement les grandes \&\#233;tapes n\&\#233;cessaires \&\#224; la construction d\&\#8217;un projet p\&\#233;dagogique fond\&\#233; sur les sciences cognitives, ainsi que les pistes p\&\#233;dagogiques les plus pratiqu\&\#233;es en la mati\&\#232;re. Enfin, il pr\&\#233;cise les possibilit\&\#233;s offertes par le recours \&\#224; l\&\#8217;intelligence artificielle dans les pratiques \&\#233;ducatives, tout en rappelant qu\&\#8217;elles ont vocation \&\#224; faciliter les apprentissages et le travail des enseignants, et non \&\#224; se substituer \&\#224; ceux-ci. Les nouvelles voies \&\#233;ducatives ouvertes par cette entr\&\#233;e des neurosciences dans les classes sont encourageantes mais n\&\#233;cessitent une formation ad hoc des \&\#233;quipes et l\&\#8217;implication de tous les acteurs du syst\&\#232;me (enseignants, \&\#233;l\&\#232;ves, encadrement), ce qui n\&\#8217;est pas rien en France\&\#160;!\&\#160;S.D.},
language = {fr},
number = {1},
urldate = {2022-04-06},
journal = {Futuribles},
author = {Berthier, Jean-Luc},
month = jul,
year = {2019},
note = {Bibliographie\_available: 0
Cairndomain: www.cairn.info
Cite Par\_available: 0
Publisher: Futuribles},
pages = {81--91},
}
@misc{alexandre_aha_2022,
type = {Le {Monde}},
title = {Aha ! {Le} cri de la créativité},
url = {https://www.lemonde.fr/blog/binaire/2022/02/04/aha-le-cri-de-la-creativite/},
abstract = {Oui, binaire s’adresse aussi aux jeunes de tous âges, que les sciences informatiques laissent parfois perplexes. Avec « Petit binaire », osons ici expliquer de manière simple et accessible, comment modéliser informatiquement la… créativité.},
language = {FR},
urldate = {2022-04-06},
journal = {Binaire},
author = {Alexandre, Frédéric and Mercier, Chloé and Viéville, Thierry},
month = feb,
year = {2022},
note = {https://hal.inria.fr/hal-03557770},
}
@article{vieville_que_2021,
title = {Que se passe-t-il dans les cerveaux des cons ?},
url = {https://hal.inria.fr/hal-03512294},
language = {fr},
urldate = {2022-04-06},
journal = {Binaire},
author = {Viéville, Thierry},
month = dec,
year = {2021},
}
@article{amidu_protocol_2019,
title = {A protocol analysis of use of forward and backward reasoning during valuation problem solving},
volume = {37},
doi = {10.1108/PM-10-2018-0056},
abstract = {Purpose
Behavioural studies of valuers have suggested that valuers rely on a number of cognitive strategies involving reasoning and intuition when undertaking a valuation task. However, there are few studies of the actual reasoning mechanisms in valuation. In other fields, much attention has been paid to forward and backward reasoning, as this shows the choices and decisions that are made in undertaking a complex task. This paper studied this during a valuation task. The purpose of this paper is twofold: first, to develop a methodological approach for empirical research on valuers’ reasoning, and, second, to report expert-novice differences on valuers’ use of forward and backward reasoning during a valuation problem solving.
Design/methodology/approach
The study utilised a verbal protocol analysis (VPA) to elicit think-aloud data from a purposive sample of a group of valuers of different levels of expertise undertaking a commercial-valuation task. Through a content analysis interpretive strategy, the transcripts were analysed into different cognitive segments identifying the forward and backward reasoning strategies.
Findings
The findings showed that valuers accomplished the valuation task by dividing the overall problem into sub-problems. These sub-problems are thereafter solved by integrating available data with existing knowledge by relying more on forward reasoning than backward reasoning. However, there were effects associated with the level of expertise in the way the processes of forward and backward reasoning are used, with the expert and intermediate valuers being more thorough and comprehensive in their reasoning process than the novices.
Research limitations/implications
This study explores the possibility that forward and backward reasoning play an important role in commercial valuation problem solving using a limited sample of valuers. Given this, data cannot be generalised to all valuation practice settings but may motivate future research that examines the effectiveness of forward and backward reasoning in diverse valuation practice settings and develops a holistic model of valuation reasoning.
Practical implications
The findings of this study are applicable to valuation practice. Future training efforts need to evaluate the usefulness of teaching problem solving and explicitly recognise forward and backward reasoning, along with other problem-solving strategies uncovered in this study, as standard training strategies for influencing the quality of valuation decisions.
Originality/value
By adopting VPA, this study employs an insightful and rich dataset which allows an interpretation of thoughts of valuers into cognitive reasoning strategies that provide a deeper level of understanding of how valuers solve valuation problem; this has not been possible in previous related valuation studies.},
journal = {Property Management},
author = {Amidu, Abdul-Rasheed and Boyd, David and Gobet, Fernand},
month = oct,
year = {2019},
pages = {638--661},
}
@article{kapoor_comparative_2016,
title = {Comparative {Study} {Of} {Forward} {And} {Backward} {Chaining} {In} {Artificial} {Intelligence}},
doi = {10.18535/Ijecs/v5i4.32},
abstract = {An artificial intelligence system is capable of elucidating and representing knowledge along with storing and manipulating data. Knowledge could be a collection of facts and principles build up by human. It is the refined form of information. Knowledge representation is to represent knowledge in a manner that facilitates the power to draw conclusions from knowledge. Knowledge representation is a good approach as conventional procedural code is not the best way to use for solving complex problems. Frames, Semantic Nets, Systems Architecture, Rules, and Ontology are its techniques to represent knowledge. Forward and backward chaining are the two main methods of reasoning used in an inference engine. It is a very common approach for "expert systems", business and systems. This paper focus on the concept of knowledge representation in artificial intelligence and the elaborating the comparison of forward and backward chaining.},
journal = {International Journal Of Engineering And Computer Science},
author = {Kapoor, Namarta and Bahl, Nischay},
month = apr,
year = {2016},
}
@article{cosgrove_quantifying_2021,
title = {Quantifying flexibility in thought: {The} resiliency of semantic networks differs across the lifespan},
volume = {211},
issn = {0010-0277},
shorttitle = {Quantifying flexibility in thought},
url = {https://www.sciencedirect.com/science/article/pii/S0010027721000500},
doi = {10.1016/j.cognition.2021.104631},
abstract = {Older adults tend to have a broader vocabulary compared to younger adults – indicating a richer storage of semantic knowledge – but their retrieval abilities decline with age. Recent advances in quantitative methods based on network science have investigated the effect of aging on semantic memory structure. However, it is yet to be determined how this aging effect on semantic memory structure relates to its overall flexibility. Percolation analysis provides a quantitative measure of the flexibility of a semantic network, by examining how a semantic memory network is resistant to “attacks” or breaking apart. In this study, we incorporated percolation analyses to examine how semantic networks of younger and older adults break apart to investigate potential age-related differences in language production. We applied the percolation analysis to 3 independent sets of data (total N = 78 younger, 78 older adults) from which we generated semantic networks based on verbal fluency performance. Across all 3 datasets, the percolation integrals of the younger adults were larger than older adults, indicating that older adults' semantic networks were less flexible and broke down faster than the younger adults'. Our findings provide quantitative evidence for diminished flexibility in older adults' semantic networks, despite the stability of semantic knowledge across the lifespan. This may be one contributing factor to age-related differences in language production.},
language = {en},
urldate = {2022-04-14},
journal = {Cognition},
author = {Cosgrove, Abigail L. and Kenett, Yoed N. and Beaty, Roger E. and Diaz, Michele T.},
month = jun,
year = {2021},
keywords = {Aging, Cognition, Percolation, Semantic networks, Verbal fluency},
pages = {104631},
}
@article{cinan_confirmatory_2013,
title = {Confirmatory factor analysis on separability of planning and insight constructs},
volume = {25},
issn = {2044-5911},
url = {https://doi.org/10.1080/20445911.2012.729035},
doi = {10.1080/20445911.2012.729035},
abstract = {This study aimed to investigate the separability of planning, a form of noninsight problem solving, from insight problem solving by means of using confirmatory factor analysis (CFA). The relationships of these two types of problem-solving tasks with meta-cognitive awareness were also assessed. Participants performed a set of planning tasks, a set of insight tasks and a self-report inventory on metacognitive ability. The CFA results revealed that planning and insight problem solving were closely related constructs and were not clearly separable. Model comparisons indicated that the fit of the alternative one-factor model was slightly better than the fit of the two-factor model. The correlational results showed that both planning task performance and insight problem-solving performance had no correlations with the metacognitive knowledge or the metacognitive regulation components of the metacognitive awareness inventory.},
number = {1},
urldate = {2022-04-14},
journal = {Journal of Cognitive Psychology},
author = {Cinan, Sevtap and Özen, Gaye and Hampshire, Adam},
month = feb,
year = {2013},
note = {Publisher: Routledge
\_eprint: https://doi.org/10.1080/20445911.2012.729035},
keywords = {Confirmatory factor analysis, Insight problem solving, Metacognitive awareness, Planning},
pages = {7--23},
}
@article{domingos_unifying_1996,
title = {Unifying instance-based and rule-based induction},
volume = {24},
issn = {0885-6125},
url = {https://doi.org/10.1023/A:1018006431188},
doi = {10.1023/A:1018006431188},
number = {2},
urldate = {2022-04-15},
journal = {Machine Language},
author = {Domingos, Pedro},
year = {1996},
keywords = {case-based reasoning, concept learning, instance-based learning, multi-strategy learning, nearest-neighbor classification, rule induction},
pages = {141--168},
}
@inproceedings{lakkaraju_rule_2000,
address = {Berlin, Heidelberg},
series = {{ISMIS} '00},
title = {Rule {Based} {Abduction}},
isbn = {978-3-540-41094-2},
doi = {https://doi.org/10.1007/3-540-39963-1_55},
abstract = {This paper introduces a procedural approach to perform rule based abduction in a knowledge base. In this context a knowledge base is realised as a normal abductive logic program, and an observation can be either a literal or a rule. A SLDNF resolution based proof procedure is employed to achieve this rule based abduction. It is shown that using this algorithm, one can always find a minimal explanation for the observation if there exists such an explanation.},
urldate = {2022-04-15},
booktitle = {Proceedings of the 12th {International} {Symposium} on {Foundations} of {Intelligent} {Systems}},
publisher = {Springer-Verlag},
author = {Lakkaraju, Sai Kiran and Zhang, Yan},
month = oct,
year = {2000},
pages = {525--533},
file = {Lakkaraju_Zhang_2000_Rule_Based_Abduction.pdf:files/7519/Lakkaraju_Zhang_2000_Rule_Based_Abduction.pdf:application/pdf},
}
@article{metcalfe_intuition_1987,
title = {Intuition in insight and noninsight problem solving},
volume = {15},
issn = {1532-5946},
url = {https://doi.org/10.3758/BF03197722},
doi = {10.3758/BF03197722},
abstract = {People’s metacognitions, both before and during problem solving, may be of importance in motivating and guiding problem-solving behavior. These metacognitions could also be diagnostic for distinguishing among different classes of problems, each perhaps controlled by different cognitive processes. In the present experiments, intuitions on classic insight problems were compared with those on noninsight and algebra problems. The findings were as follows: (1) subjective feeling of knowing predicted performance on algebra problems but not on insight problems; (2) subjects’ expectations of performance greatly exceeded their actual performance, especially on insight problems; (3) normative predictions provided a better estimate of individual performance than did subjects’ own predictions, especially on the insight problems; and, most importantly, (4) the patterns-of-warmth ratings, which reflect subjects’ feelings of approaching solution, differed for insight and noninsight problems. Algebra problems and noninsight problems showed a more incremental pattern over the course of solving than did insight problems. In general, then, the data indicated that noninsight problems were open to accurate predictions of performance, whereas insight problems were opaque to such predictions. Also, the phenomenology of insight-problem solution was characterized by a sudden, unforeseen flash of illumination. We propose that the difference in phenomenology accompanying insight and noninsight problem solving, as empirically demonstrated here, be used to define insight.},
language = {en},
number = {3},
urldate = {2022-04-19},
journal = {Memory \& Cognition},
author = {Metcalfe, Janet and Wiebe, David},
month = may,
year = {1987},
keywords = {Dividual Performance, Insight Problem, Journal ofExperimental Psychology, Normative Prediction, Water Lily},
pages = {238--246},
}
@article{zemla_estimating_2018,
title = {Estimating {Semantic} {Networks} of {Groups} and {Individuals} from {Fluency} {Data}},
volume = {1},
issn = {2522-087X},
url = {https://doi.org/10.1007/s42113-018-0003-7},
doi = {10.1007/s42113-018-0003-7},
abstract = {One popular and classic theory of how the mind encodes knowledge is an associative semantic network, where concepts and associations between concepts correspond to nodes and edges, respectively. A major issue in semantic network research is that there is no consensus among researchers as to the best method for estimating the network of an individual or group. We propose a novel method (U-INVITE) for estimating semantic networks from semantic fluency data (listing items from a category) based on a censored random walk model of memory retrieval. We compare this method to several other methods in the literature for estimating networks from semantic fluency data. In simulations, we find that U-INVITE can recover semantic networks with low error rates given only a moderate amount of data. U-INVITE is the only known method derived from a psychologically plausible process model of memory retrieval and one of two known methods that we found to be consistent estimators of this process: if semantic memory retrieval is consistent with this process, the procedure will eventually estimate the true network (given enough data). We conduct the first exploration of different methods for estimating psychologically valid semantic networks by comparing people’s similarity judgments of edges estimated by each network estimation method. To encourage best practices, we discuss the merits of each network estimation technique, provide a flow chart that assists with choosing an appropriate method, and supply code for others to employ these techniques on their own data.},
language = {en},
number = {1},
urldate = {2022-04-18},
journal = {Computational Brain \& Behavior},
author = {Zemla, Jeffrey C. and Austerweil, Joseph L.},
month = mar,
year = {2018},
keywords = {Methodology, Knowledge representation, Semantic networks, Bayesian modeling, Fluency},
pages = {36--58},
}
@incollection{dubitzky_towards_2012,
title = {Towards {Creative} {Information} {Exploration} {Based} on {Koestler}'s {Concept} of {Bisociation}},
abstract = {Creative information exploration refers to a novel framework for exploring large volumes of heterogeneous information. In particular, creative information exploration seeks to discover new, surprising and valuable relationships in data that would not be revealed by conventional information retrieval, data mining and data analysis technologies. While our approach is inspired by work in the field of computational creativity, we are particularly interested in a model of creativity proposed by Arthur Koestler in the 1960s. Koestler's model of creativity rests on the concept of bisociation. Bisociative thinking occurs when a problem, idea, event or situation is perceived simultaneously in two or more "matrices of thought" or domains. When two matrices of thought interact with each other, the result is either their fusion in a novel intellectual synthesis or their confrontation in a new aesthetic experience. This article discusses some of the foundational issues of computational creativity and bisociation in the context of creative information exploration.},
booktitle = {Bisociative {Knowledge} {Discovery}},
author = {Dubitzky, Werner and Kötter, Tobias and Schmidt, Oliver and Berthold, Michael},
month = jan,
year = {2012},
doi = {10.1007/978-3-642-31830-6_2},
note = {Journal Abbreviation: Bisociative Knowledge Discovery},
pages = {11--32},
}
@article{fauconnier_conceptual_2003,
title = {Conceptual {Blending}, {Form} and {Meaning}},
volume = {19},
doi = {10.14428/rec.v19i19.48413},
journal = {Recherches en Communication; No 19: Sémiotique cognitive — Cognitive Semiotics; 57-86},
author = {Fauconnier, Gilles and Turner, Mark},
month = mar,
year = {2003},
}
@article{lieto_description_2020,
title = {A description logic framework for commonsense conceptual combination integrating typicality, probabilities and cognitive heuristics},
volume = {32},
issn = {0952-813X},
url = {https://doi.org/10.1080/0952813X.2019.1672799},
doi = {10.1080/0952813X.2019.1672799},
abstract = {We propose a nonmonotonic Description Logic of typicality able to account for the phenomenon of the combination of prototypical concepts. The proposed logic relies on the logic of typicality ALC+TR, whose semantics is based on the notion of rational closure, as well as on the distributed semantics of probabilistic Description Logics, and is equipped with a cognitive heuristic used by humans for concept composition.We first extend the logic of typicality ALC+TR by typicality inclusions of the form p::T(C)⊑D, whose intuitive meaning is that ‘we believe with degree p about the fact that typical Cs are Ds’. As in the distributed semantics, we define different scenarios containing only some typicality inclusions, each one having a suitable probability. We then exploit such scenarios in order to ascribe typical properties to a concept C obtained as the combination of two prototypical concepts. We also show that reasoning in the proposed Description Logic is ExpTime-complete as for the underlying standard Description Logic ALC.},
number = {5},
urldate = {2022-05-10},
journal = {Journal of Experimental \& Theoretical Artificial Intelligence},
author = {Lieto, Antonio and Pozzato, Gian Luca},
month = sep,
year = {2020},
note = {Publisher: Taylor \& Francis
\_eprint: https://doi.org/10.1080/0952813X.2019.1672799},
keywords = {cognitive modelling, common-sense reasoning, description logics, Nonmonotonic reasoning},
pages = {769--804},
}
@article{lieto_beyond_2019,
title = {Beyond subgoaling: {A} dynamic knowledge generation framework for creative problem solving in cognitive architectures},
volume = {58},
issn = {1389-0417},
shorttitle = {Beyond subgoaling},
url = {https://www.sciencedirect.com/science/article/pii/S1389041719304632},
doi = {10.1016/j.cogsys.2019.08.005},
abstract = {In this paper we propose a computational framework aimed at extending the problem solving capabilities of cognitive artificial agents through the introduction of a novel, goal-directed, dynamic knowledge generation mechanism obtained via a non monotonic reasoning procedure. In particular, the proposed framework relies on the assumption that certain classes of problems cannot be solved by simply learning or injecting new external knowledge in the declarative memory of a cognitive artificial agent but, on the other hand, require a mechanism for the automatic and creative re-framing, or re-formulation, of the available knowledge. We show how such mechanism can be obtained trough a framework of dynamic knowledge generation that is able to tackle the problem of commonsense concept combination. In addition, we show how such a framework can be employed in the field of cognitive architectures in order to overcome situations like the impasse in SOAR by extending the possible options of its subgoaling procedures.},
language = {en},
urldate = {2022-05-10},
journal = {Cognitive Systems Research},
author = {Lieto, Antonio and Perrone, Federico and Pozzato, Gian Luca and Chiodino, Eleonora},
month = dec,
year = {2019},
keywords = {Representation, Cognitive architectures, Commonsense reasoning, Concept combination, Knowledge generation},
pages = {305--316},
}
@article{woltering_neuroscience_2016,
title = {On the {Neuroscience} of {Self}-{Regulation} in {Children} {With} {Disruptive} {Behavior} {Problems}: {Implications} for {Education}},
volume = {86},
issn = {0034-6543},
shorttitle = {On the {Neuroscience} of {Self}-{Regulation} in {Children} {With} {Disruptive} {Behavior} {Problems}},
url = {https://doi.org/10.3102/0034654316673722},
doi = {10.3102/0034654316673722},
abstract = {Self-regulation is increasingly recognized as a key predictor of academic and social competence. A multidisciplinary understanding of this ability is timely and can strengthen theory and practice. The present review aims to inform educators on what cognitive neuroscience can teach us about self-regulation. To do so, we will focus on a decade-long research program examining children with disruptive behavior problems and their peers, and ask whether neural measures of self-regulation can (a) covary with individual differences in behavioral measures of self-regulation, (b) trace developmental patterns, and (c) predict or trace behavioral change with successful treatment of disruptive behavior problems. We show that several studies begin to converge on a set of neural measures derived from the prefrontal cortex that can be consistently linked to processes of self-regulation. Next, we will discuss what these measures mean from a cognitive neuroscience perspective and how this knowledge could influence and/or support psychological models relevant to education.},
language = {en},
number = {4},
urldate = {2022-05-13},
journal = {Review of Educational Research},
author = {Woltering, Steven and Shi, Qinxin},
month = dec,
year = {2016},
note = {Publisher: American Educational Research Association},
keywords = {neuroscience, development, education, treatment, self-regulation},
pages = {1085--1110},
}
@article{kupers_childrens_2019,
title = {Children’s {Creativity}: {A} {Theoretical} {Framework} and {Systematic} {Review}},
volume = {89},
issn = {0034-6543},
shorttitle = {Children’s {Creativity}},
url = {https://doi.org/10.3102/0034654318815707},
doi = {10.3102/0034654318815707},
abstract = {Within education, the importance of creativity is recognized as an essential 21st-century skill. Based on this premise, the first aim of this article is to provide a theoretical integration through the development of a framework based on the principles of complex dynamic systems theory, which describes and explains children’s creativity. This model is used to explain differing views on the role of education in developing children’s creativity. Our second aim is empirical integration. On the basis of a three-dimensional taxonomy, we performed a systematic review of the recent literature (2006–2017, 184 studies) on primary school students’ creativity. Our results show that creativity is most often measured as a static, aggregated construct. In line with our theoretical model, we suggest ways that future research can elaborate on the moment-to-moment interactions that form the basis of long-term creative development, as well as on the mechanisms that connect different levels of creativity.},
language = {en},
number = {1},
urldate = {2022-05-13},
journal = {Review of Educational Research},
author = {Kupers, Elisa and Lehmann-Wermser, Andreas and McPherson, Gary and van Geert, Paul},
month = feb,
year = {2019},
note = {Publisher: American Educational Research Association},
keywords = {primary education, creativity, complex dynamic systems, emergence},
pages = {93--124},
}
@article{thurlings_toward_2015,
title = {Toward a {Model} of {Explaining} {Teachers}’ {Innovative} {Behavior}: {A} {Literature} {Review}},
volume = {85},
issn = {0034-6543},
shorttitle = {Toward a {Model} of {Explaining} {Teachers}’ {Innovative} {Behavior}},
url = {https://doi.org/10.3102/0034654314557949},
doi = {10.3102/0034654314557949},
abstract = {Innovative behavior can be described as a process in which new ideas are generated, created, developed, applied, promoted, realized, and modified by employees to benefit role performance. Various reasons, such as rapid technological and social changes in society, underline the necessity for innovative behavior of employees and certainly of teachers. However, little research has been conducted that explores teacher innovative behavior and which factors influence this behavior or what effects can be achieved through such behavior. In this systematic literature review, we develop a preliminary model of factors that enhance innovative behavior in educational organizations. Similar to findings of studies in other human behavior fields, self-efficacy plays an important role as well as a variety of individual and environmental factors. Based on this review, we urge for more systematic research on teacher innovative behavior to enhance the future quality of education.},
language = {en},
number = {3},
urldate = {2022-05-13},
journal = {Review of Educational Research},
author = {Thurlings, Marieke and Evers, Arnoud T. and Vermeulen, Marjan},
month = sep,
year = {2015},
note = {Publisher: American Educational Research Association},
keywords = {education, innovative behavior, systematic literature review, teachers},
pages = {430--471},
}
@article{mansfield_effectiveness_1978,
title = {The {Effectiveness} of {Creativity} {Training}},
volume = {48},
issn = {0034-6543},
url = {https://doi.org/10.3102/00346543048004517},
doi = {10.3102/00346543048004517},
language = {en},
number = {4},
urldate = {2022-05-13},
journal = {Review of Educational Research},
author = {Mansfield, Richard S. and Busse, Thomas V. and Krepelka, Ernest J.},
month = dec,
year = {1978},
note = {Publisher: American Educational Research Association},
pages = {517--536},
}
@incollection{gruszka_4ps_2017,
title = {The {4P}’s {Creativity} {Model} and its application in different fields.},
isbn = {978-981-314-187-2},
abstract = {The aim of this chapter is to introduce the 4P’s Model of Creativity (Rhodes, 1961) and to review its practical implications in different fields, including education, business, engineering, and others. According to this model, creativity can be viewed from four different perspectives: product, process, person and press of the environment. Thus, the main question tackled here is how creativity can be stimulated by attending to each of these components.},
booktitle = {Handbook of the {Management} of {Creativity} and {Innovation}},
publisher = {World Scientific Press},
author = {Gruszka, Aleksandra and Tang, Min},
month = may,
year = {2017},
pages = {51--71},
}
@article{liu_motivational_2016,
title = {Motivational mechanisms of employee creativity: {A} meta-analytic examination and theoretical extension of the creativity literature},
volume = {137},
issn = {0749-5978},
shorttitle = {Motivational mechanisms of employee creativity},
url = {https://www.sciencedirect.com/science/article/pii/S0749597816304794},
doi = {10.1016/j.obhdp.2016.08.001},
abstract = {Drawing on the componential theory of creativity, social cognitive theory, and prosocial motivation theory, we examined intrinsic motivation, creative self-efficacy, and prosocial motivation as distinct motivational mechanisms underlying creativity. Results from a meta-analysis of 191 independent samples (N=51,659) documented in the relevant literature revealed that intrinsic motivation, creative self-efficacy, and prosocial motivation each had unique explanatory power in predicting creativity, and that the three motivational mechanisms functioned differently as mediators between contextual and personal factors and creativity. The relationships of intrinsic motivation and creative self-efficacy with creativity also were found to be contingent upon sample characteristics and methodological factors (i.e., national culture, creativity measure, intrinsic motivation and creative self-efficacy measures, and publication status). Our findings highlight the need to develop a more fine-grained theory of motivation and creativity. Implications for theoretical extensions and future research are discussed.},
language = {en},
urldate = {2022-05-23},
journal = {Organizational Behavior and Human Decision Processes},
author = {Liu, Dong and Jiang, Kaifeng and Shalley, Christina E. and Keem, Sejin and Zhou, Jing},
month = nov,
year = {2016},
keywords = {Creativity, Intrinsic motivation, Creative self-efficacy, Prosocial motivation},
pages = {236--263},
}
@article{rhodes_analysis_1961,
title = {An {Analysis} of {Creativity}},
volume = {42},
issn = {0031-7217},
url = {https://www.jstor.org/stable/20342603},
number = {7},
urldate = {2022-05-23},
journal = {The Phi Delta Kappan},
author = {Rhodes, Mel},
year = {1961},
note = {Publisher: Phi Delta Kappa International},
pages = {305--310},
}
@article{luce_using_2016,
title = {Using {Indirect} vs. {Direct} {Measures} in the {Summative} {Assessment} of {Student} {Learning} in {Higher} {Education}},
volume = {16},
copyright = {Copyright (c) 2016 Christine Luce, Jean P Kirnan},
issn = {1527-9316},
url = {https://scholarworks.iu.edu/journals/index.php/josotl/article/view/19371},
doi = {10.14434/josotl.v16i4.19371},
abstract = {Contradictory results have been reported regarding the accuracy of various methods used to assess student learning in higher education. The current study examined student learning outcomes across a multi-section and multi-instructor psychology research course with both indirect and direct assessments in a sample of 67 undergraduate students. The indirect method measured student perceived knowledge and abilities on course topics, while the direct method measured actual knowledge where students answered test questions or solved problems reflecting course content. Both measures independently demonstrated increases from pretest to posttest; however the indirect measure did not correlate with final course grades. Results also showed respondents scoring lower on the direct measure were overconfident (as measured by indirect score) in their perceived knowledge and ability, the Dunning-Kruger Effect. Based on our findings, we concluded that the indirect method was not an accurate measure of student learning, but may have benefits as an instructional tool.},
language = {en},
number = {4},
urldate = {2022-05-16},
journal = {Journal of the Scholarship of Teaching and Learning},
author = {Luce, Christine and Kirnan, Jean P.},
month = aug,
year = {2016},
note = {Number: 4},
keywords = {higher education},
pages = {75--91},
}
@misc{hoffmann_influence_2011,
type = {info:eu-repo/semantics/{bachelorThesis}},
title = {The influence of different forms of camera surveillance and personality characteristics on deviant and prosocial behaviour},
url = {https://essay.utwente.nl/61250/},
abstract = {Personality characteristics of 86 students were measured, who were then randomly assigned to three different camera conditions and one control condition. They were asked to solve a couple of puzzles but were given the chance to cheat in various ways. Apart from that situations were set up in which participants had the possibility to show pro-social behaviour. The results show that cheating behaviour decreases the more control is indicated by the presence and presentation of the camera. Interaction effects of camera condition and personality characteristics on both cheating and pro-social behaviour were found. Further research is needed to use surveillance cameras more efficient.},
language = {en},
urldate = {2022-05-17},
author = {Hoffmann, C.},
month = oct,
year = {2011},
note = {Publisher: University of Twente},
}
@article{latane_social_1981,
title = {The social impact of majorities and minorities},
volume = {88},
issn = {1939-1471},
doi = {10.1037/0033-295X.88.5.438},
abstract = {Reviews 2 traditional lines of research on social influence processes—research on conformity, which looks at the influence of the majority on a passive minority, and research on innovation, which considers the influence of active minorities on a silent majority. A new theory of social impact is examined that views social influence as resulting from forces operating in a social force field. It proposes that influence by either a majority or a minority will be a multiplicative function of the strength, immediacy, and number of its members. It is suggested that social impact theory offers a general model of social influence processes that integrates previous theoretical formulations and empirical findings and accounts for the reciprocal influence of majorities and minorities. Thus, by viewing social influence as a unitary concept, social impact theory permits comparisons between conformity and innovation and predicts the relative magnitude of their effects. (39 ref) (PsycINFO Database Record (c) 2016 APA, all rights reserved)},
number = {5},
journal = {Psychological Review},
author = {Latané, Bibb and Wolf, Sharon},
year = {1981},
note = {Place: US
Publisher: American Psychological Association},
keywords = {Theories, Minority Groups, Social Groups, Social Influences},
pages = {438--453},
}
@article{zhang_toward_2017,
title = {Toward a {Reliable} {Collection} of {Eye}-{Tracking} {Data} for {Image} {Quality} {Research}: {Challenges}, {Solutions}, and {Applications}},
volume = {26},
issn = {1941-0042},
shorttitle = {Toward a {Reliable} {Collection} of {Eye}-{Tracking} {Data} for {Image} {Quality} {Research}},
doi = {10.1109/TIP.2017.2681424},
abstract = {Image quality assessment potentially benefits from the addition of visual attention. However, incorporating aspects of visual attention in image quality models by means of a perceptually optimized strategy is largely unexplored. Fundamental challenges, such as how visual attention is affected by the concurrence of visual signals and their distortions; whether visual attention affected by distortion or that driven by the original scene only should be included in an image quality model; and how to select visual attention models for the image quality application context, remain. To shed light on the above unsolved issues, designing and performing eye-tracking experiments are essential. Collecting eye-tracking data for the purpose of image quality study is so far confronted with a bias due to the involvement of stimulus repetition. In this paper, we propose a new experimental methodology to eliminate such inherent bias. This allows obtaining reliable eye-tracking data with a large degree of stimulus variability. In fact, we first conducted 5760 eye movement trials that included 160 human observers freely viewing 288 images of varying quality. We then made use of the resulting eye-tracking data to provide insights into the optimal use of visual attention in image quality research. The new eye-tracking data are made publicly available to the research community.},
number = {5},
journal = {IEEE Transactions on Image Processing},
author = {Zhang, Wei and Liu, Hantao},
month = may,
year = {2017},
note = {Conference Name: IEEE Transactions on Image Processing},
keywords = {gaze, fixation, Data models, Databases, Dispersion, Distortion, eye-tracking, image quality, Image quality, Observers, saliency, Visual attention, Visualization},
pages = {2424--2437},
}
@article{van_rompay_eye_2009,
title = {The {Eye} of the {CameraEffects} of {Security} {Cameras} on {Prosocial} {Behavior}},
volume = {41},
doi = {10.1177/0013916507309996},
abstract = {This study addresses the effects of security cameras on prosocial behavior. Results from previous studies indicate that the presence of others can trigger helping behavior, arising from the need for approval of others. Extending these findings, the authors propose that security cameras can likewise trigger such approval-seeking behaviors by implying the presence of a watchful eye. Because people vary in the extent to which they strive for others' approval, it was expected that the effects of security cameras on prosocial behavior vary with participants' need for approval. To test these predictions, an experimental study was conducted with “presence of security camera” and “need for approval” as independent variables. Results showed that participants indeed offered more help in the presence of a security camera but only to the extent that this helping involved public or observable behavior. As expected, this effect was more pronounced for individuals high in need for approval. Practical implications and suggestions for future research are discussed.},
journal = {Environment and Behavior - ENVIRON BEHAV},
author = {Van Rompay, Thomas and Vonk, Dorette and Fransen, Marieke},
month = jan,
year = {2009},
pages = {60--74},
}
@article{yu_being_2015,
title = {Being watched by others eliminates the effect of emotional arousal on inhibitory control},
volume = {6},
issn = {1664-1078},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4299288/},
doi = {10.3389/fpsyg.2015.00004},
abstract = {The psychological effect of being watched by others has been proven a powerful tool in modulating social behaviors (e.g., charitable giving) and altering cognitive performance (e.g., visual search). Here we tested whether such awareness would affect one of the core elements of human cognition: emotional processing and impulse control. Using an emotion stop-signal paradigm, we found that viewing emotionally-arousing erotic images before attempting to inhibit a motor response impaired participants’ inhibition ability, but such an impairing effect was completely eliminated when participants were led to believe that their facial expressions were monitored by a webcam. Furthermore, there was no post-error slowing in any of the conditions, thus these results cannot be explained by a deliberate speed-accuracy tradeoff or other types of conscious shift in strategy. Together, these findings demonstrate that the interaction between emotional arousal and impulse control can be dependent on one’s state of self-consciousness. Furthermore, this study also highlights the effect that the mere presence of the experimenter may have on participants’ cognitive performance, even if it’s only a webcam.},
urldate = {2022-05-04},
journal = {Frontiers in Psychology},
author = {Yu, Jiaxin and Tseng, Philip and Muggleton, Neil G. and Juan, Chi-Hung},
month = jan,
year = {2015},
pmid = {25653635},
pmcid = {PMC4299288},
pages = {4},
}
@article{king_improving_2019,
title = {Improving {Visual} {Behavior} {Research} in {Communication} {Science}: {An} {Overview}, {Review}, and {Reporting} {Recommendations} for {Using} {Eye}-{Tracking} {Methods}},
volume = {13},
issn = {1931-2458},
shorttitle = {Improving {Visual} {Behavior} {Research} in {Communication} {Science}},
url = {https://doi.org/10.1080/19312458.2018.1558194},
doi = {10.1080/19312458.2018.1558194},
abstract = {Eye tracking offers researchers an opportunity to collect an objective assessment of visual behavior. Visual behavior—referring broadly to metrics and measures of gaze positioning and movement—has been used to assess variables including exposure time, cognitive processing, prominence, and (visual) attention. Over the past decade, communication science researchers have increased their use of eye-tracking methods in published articles. During that same period, technological innovations have made eye-tracking units more affordable and accessible to interested researchers increasing the likelihood that eye-tracking research will continue to increase in the field. In this article, we provide information on eye tracking in hopes of improving the quality and reporting of eye-tracking research in communication. The article first provides an overview of basic eye-tracking information followed by a systematic review on the reporting of eye-tracking methods in communication-relevant research. We then provide eye-tracking research reporting recommendations and some ideas about how eye tracking might be integrated into scholarly work moving forward with the aim of improving the transparency and replicability of eye-tracking research in communication science.},
number = {3},
urldate = {2022-05-04},
journal = {Communication Methods and Measures},
author = {King, Andy J. and Bol, Nadine and Cummins, R. Glenn and John, Kevin K.},
month = jul,
year = {2019},
note = {Publisher: Routledge
\_eprint: https://doi.org/10.1080/19312458.2018.1558194},
pages = {149--177},
}
@article{carter_best_2020,
title = {Best practices in eye tracking research},
volume = {155},
issn = {0167-8760},
url = {https://www.sciencedirect.com/science/article/pii/S0167876020301458},
doi = {10.1016/j.ijpsycho.2020.05.010},
abstract = {This guide describes best practices in using eye tracking technology for research in a variety of disciplines. A basic outline of the anatomy and physiology of the eyes and of eye movements is provided, along with a description of the sorts of research questions eye tracking can address. We then explain how eye tracking technology works and what sorts of data it generates, and provide guidance on how to select and use an eye tracker as well as selecting appropriate eye tracking measures. Challenges to the validity of eye tracking studies are described, along with recommendations for overcoming these challenges. We then outline correct reporting standards for eye tracking studies.},
language = {en},
urldate = {2022-05-04},
journal = {International Journal of Psychophysiology},
author = {Carter, Benjamin T. and Luke, Steven G.},
month = sep,
year = {2020},
keywords = {Best practices, Eye movements, Eye tracking, Open Science, Pupillometry},
pages = {49--62},
}
@article{bacon_comparing_2011,
title = {Comparing {Direct} {Versus} {Indirect} {Measures} of the {Pedagogical} {Effectiveness} of {Team} {Testing}},
volume = {33},
issn = {0273-4753},
url = {https://doi.org/10.1177/0273475311420243},
doi = {10.1177/0273475311420243},
abstract = {Direct measures (tests) of the pedagogical effectiveness of team testing and indirect measures (student surveys) of pedagogical effectiveness of team testing were collected in several sections of an undergraduate marketing course with varying levels of the use of team testing. The results indicate that although students perceived team testing to have a substantial impact on their learning, this pedagogy in fact had no impact on direct measures of learning. In an additional analysis, the performance of the team on the group test was best predicted by the best individual performance on the team. Possible explanations and directions for future research are discussed.},
language = {en},
number = {3},
urldate = {2022-05-16},
journal = {Journal of Marketing Education},
author = {Bacon, Donald R.},
month = dec,
year = {2011},
note = {Publisher: SAGE Publications Inc},
keywords = {collaborative learning, cooperative learning, assessment, student groups, team testing},
pages = {348--358},
}
@article{zwickel_how_2010,
title = {How the presence of persons biases eye movements},
volume = {17},
issn = {1531-5320},
url = {https://doi.org/10.3758/PBR.17.2.257},
doi = {10.3758/PBR.17.2.257},
abstract = {We investigated modulation of gaze behavior of observers viewing complex scenes that included a person. To assess spontaneous orientation-following, and in contrast to earlier studies, we did not make the person salient via instruction or low-level saliency. Still, objects that were referred to by the orientation of the person were visited earlier, more often, and longer than when they were not referred to. Analysis of fixation sequences showed that the number of saccades to the cued and uncued objects differed only for saccades that started from the head region, but not for saccades starting from a control object or from a body region. We therefore argue that viewing a person leads to an increase in spontaneous following of the person’s viewing direction even when the person plays no role in scene understanding and is not made prominent.},
language = {en},
number = {2},
urldate = {2022-05-04},
journal = {Psychonomic Bulletin \& Review},
author = {Zwickel, Jan and L.-H. Võ, Melissa},
month = apr,
year = {2010},
keywords = {Complex Scene, Head Area, Head Region, Overt Attention, Visual Cognition},
pages = {257--262},
}
@article{birmingham_social_2008,
title = {Social {Attention} and {Real}-{World} {Scenes}: {The} {Roles} of {Action}, {Competition} and {Social} {Content}},
volume = {61},
issn = {1747-0218},
shorttitle = {Social {Attention} and {Real}-{World} {Scenes}},
url = {https://doi.org/10.1080/17470210701410375},
doi = {10.1080/17470210701410375},
abstract = {The present study examined how social attention is influenced by social content and the presence of items that are available for attention. We monitored observers’ eye movements while they freely viewed real-world social scenes containing either 1 or 3 people situated among a variety of objects. Building from the work of Yarbus (1965/1967) we hypothesized that observers would demonstrate a preferential bias to fixate the eyes of the people in the scene, although other items would also receive attention. In addition, we hypothesized that fixations to the eyes would increase as the social content (i.e., number of people) increased. Both hypotheses were supported by the data, and we also found that the level of activity in the scene influenced attention to eyes when social content was high. The present results provide support for the notion that the eyes are selected by others in order to extract social information. Our study also suggests a simple and surreptitious methodology for studying social attention to real-world stimuli in a range of populations, such as those with autism spectrum disorders.},
language = {en},
number = {7},
urldate = {2022-05-05},
journal = {Quarterly Journal of Experimental Psychology},
author = {Birmingham, Elina and Bischof, Walter F. and Kingstone, Alan},
month = jul,
year = {2008},
note = {Publisher: SAGE Publications},
pages = {986--998},
}
@article{kao_effects_2021,
title = {The effects of observation in video games: how remote observation influences player experience, motivation, and behaviour},
volume = {0},
issn = {0144-929X},
shorttitle = {The effects of observation in video games},
url = {https://doi.org/10.1080/0144929X.2021.1906321},
doi = {10.1080/0144929X.2021.1906321},
abstract = {Surveillance is ubiquitous. It is well known that the presence of other people (in-person or remote, actual or perceived) increases performance on simple tasks and decreases performance in complex tasks (Zajonc 1965). But little is known about these phenomena in the context of video games, with recent advances finding that they do not necessarily extend to games (Emmerich and Masuch 2018). In Experiment 1 (N=1489; No Observation vs. Researcher Observing), we find that participants observed by a researcher played significantly longer, and performed significantly better, across three video games. Moreover, we find some support that participants observed by a researcher score higher on player experience and intrinsic motivation. In Experiment 2 (N=843; Researcher Observing vs. Professor Observing), we seek to understand whether different roles differing in their perceived evaluativeness would influence the effects of observation. We find that participants observed by a professor had, at times, significantly lower performance, player experience, intrinsic motivation, playing time, and higher anxiety. In Experiment 3 (N=1358; No Observation vs. Researcher Observing), we further validate Experiment 1 by extending our results to three additional game genres. Here, we provide the largest study on observation in video games to date. The study is also the first to show that observer type can significantly influence player outcomes.},
number = {0},
urldate = {2022-05-05},
journal = {Behaviour \& Information Technology},
author = {Kao, Dominic},
month = apr,
year = {2021},
note = {Publisher: Taylor \& Francis
\_eprint: https://doi.org/10.1080/0144929X.2021.1906321},
keywords = {Video games, behaviour, observation, player experience, social facilitation, surveillance},
pages = {1--23},
}
@article{risko_eyes_2011,
title = {Eyes wide shut: implied social presence, eye tracking and attention},
volume = {73},
issn = {1943-393X},
shorttitle = {Eyes wide shut},
url = {https://doi.org/10.3758/s13414-010-0042-1},
doi = {10.3758/s13414-010-0042-1},
abstract = {People often behave differently when they know they are being watched. Here, we report the first investigation of whether such social presence effects also influence looking behavior—a popular measure of attention allocation. We demonstrate that wearing an eye tracker, an implied social presence, leads individuals to avoid looking at particular stimuli. These results demonstrate that an implied social presence, here an eye tracker, can alter looking behavior. These data provide a new manipulation of social attention, as well as presenting a methodological challenge to researchers using eye tracking.},
language = {en},
number = {2},
urldate = {2022-05-04},
journal = {Attention, Perception, \& Psychophysics},
author = {Risko, Evan F. and Kingstone, Alan},
month = feb,
year = {2011},
keywords = {Attention, Eye tracking, Social cognition},
pages = {291--296},
}
@incollection{eisenberg_prosocial_2006,
address = {Washington, DC, US},
title = {Prosocial {Behavior}},
isbn = {978-0-932955-79-1},
abstract = {Although prosocial development in children is likely partly the result of factors other than socialization, it appears that adults can foster prosocial tendencies by using a variety of socialization practices. Although many people and factors clearly play a role in the development of prosocial actions, motives, and reasoning, schools, teachers, and parents can also play a role in enhancing prosocial development. This chapter focuses on identifying effective means of promoting prosocial behavior. (PsycINFO Database Record (c) 2019 APA, all rights reserved)},
booktitle = {Children's needs {III}: {Development}, prevention, and intervention},
publisher = {National Association of School Psychologists},
author = {Eisenberg, Nancy},
year = {2006},
keywords = {Childhood Development, Prosocial Behavior, Psychosocial Development, Socialization},
pages = {313--324},
}
@article{valtakari_eye_2021,
title = {Eye tracking in human interaction: {Possibilities} and limitations},
volume = {53},
issn = {1554-3528},
shorttitle = {Eye tracking in human interaction},
url = {https://doi.org/10.3758/s13428-020-01517-x},
doi = {10.3758/s13428-020-01517-x},
abstract = {There is a long history of interest in looking behavior during human interaction. With the advance of (wearable) video-based eye trackers, it has become possible to measure gaze during many different interactions. We outline the different types of eye-tracking setups that currently exist to investigate gaze during interaction. The setups differ mainly with regard to the nature of the eye-tracking signal (head- or world-centered) and the freedom of movement allowed for the participants. These features place constraints on the research questions that can be answered about human interaction. We end with a decision tree to help researchers judge the appropriateness of specific setups.},
language = {en},
number = {4},
urldate = {2022-05-04},
journal = {Behavior Research Methods},
author = {Valtakari, Niilo V. and Hooge, Ignace T. C. and Viktorsson, Charlotte and Nyström, Pär and Falck-Ytter, Terje and Hessels, Roy S.},
month = aug,
year = {2021},
keywords = {Eye tracking, Data analysis, Data quality, Human interaction, Wearable},
pages = {1592--1608},
}
@article{bergmann_exploring_2014,
title = {Exploring the {Use} of {Sensors} to {Measure} {Behavioral} {Interactions}: {An} {Experimental} {Evaluation} of {Using} {Hand} {Trajectories}},
volume = {9},
issn = {1932-6203},
shorttitle = {Exploring the {Use} of {Sensors} to {Measure} {Behavioral} {Interactions}},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3917885/},
doi = {10.1371/journal.pone.0088080},
abstract = {Humans appear to be sensitive to relative small changes in their surroundings. These changes are often initially perceived as irrelevant, but they can cause significant changes in behavior. However, how exactly people’s behavior changes is often hard to quantify. A reliable and valid tool is needed in order to address such a question, ideally measuring an important point of interaction, such as the hand. Wearable-body-sensor systems can be used to obtain valuable, behavioral information. These systems are particularly useful for assessing functional interactions that occur between the endpoints of the upper limbs and our surroundings. A new method is explored that consists of computing hand position using a wearable sensor system and validating it against a gold standard reference measurement (optical tracking device). Initial outcomes related well to the gold standard measurements (r = 0.81) showing an acceptable average root mean square error of 0.09 meters. Subsequently, the use of this approach was further investigated by measuring differences in motor behavior, in response to a changing environment. Three subjects were asked to perform a water pouring task with three slightly different containers. Wavelet analysis was introduced to assess how motor consistency was affected by these small environmental changes. Results showed that the behavioral motor adjustments to a variable environment could be assessed by applying wavelet coherence techniques. Applying these procedures in everyday life, combined with correct research methodologies, can assist in quantifying how environmental changes can cause alterations in our motor behavior.},
number = {2},
urldate = {2022-05-03},
journal = {PLoS ONE},
author = {Bergmann, Jeroen H. M. and Langdon, Patrick M. and Mayagoitia, Ruth E. and Howard, Newton},
month = feb,
year = {2014},
pmid = {24516583},
pmcid = {PMC3917885},
pages = {e88080},
}
@article{belopolsky_role_2008,
title = {The {Role} of {Awareness} in {Processing} of {Oculomotor} {Capture}: {Evidence} from {Event}-related {Potentials}},
volume = {20},
issn = {0898-929X},
shorttitle = {The {Role} of {Awareness} in {Processing} of {Oculomotor} {Capture}},
url = {https://doi.org/10.1162/jocn.2008.20161},
doi = {10.1162/jocn.2008.20161},
abstract = {Previous research has shown that task-irrelevant onsets trigger an eye movement in their direction. Such oculomotor capture is often impervious to conscious awareness. The present study used event-related brain potentials to examine how such oculomotor errors are detected, evaluated, and compensated for and whether awareness of an error played a role at any of these stages of processing. The results show that the early processes of error detection and correction (as represented by the error-related negativity and the parietal N1) are not directly affected by subjective awareness of making an error. Instead, they seem to be modulated by the degree of temporal overlap between the programming of the correct and erroneous saccade. We found that only a later component (the error-related positivity [Pe]) is modulated by awareness of making an erroneous eye movement. We propose that awareness of oculomotor capture primarily depends on this later process.},
number = {12},
urldate = {2022-05-05},
journal = {Journal of Cognitive Neuroscience},
author = {Belopolsky, Artem V. and Kramer, Arthur F. and Theeuwes, Jan},
month = dec,
year = {2008},
pages = {2285--2297},
}
@inproceedings{haro_non-invasive_2000,
address = {New York, NY, USA},
series = {{CHI} {EA} '00},
title = {A non-invasive computer vision system for reliable eye tracking},
isbn = {978-1-58113-248-9},
url = {https://doi.org/10.1145/633292.633385},
doi = {10.1145/633292.633385},
abstract = {Knowing what the user is attending to and what they are looking at is essential for creating attentive user interfaces. Towards this end, we are building a reliable, real-time, non-invasive eye tracker using computer vision. Our system can robustly locate and track eyes without any calibration, and estimate the user's focus of attention. We have built several higher-level processes on top of this tracking system and have done some user studies to test the viability of our approach.},
urldate = {2022-05-03},
booktitle = {{CHI} '00 {Extended} {Abstracts} on {Human} {Factors} in {Computing} {Systems}},
publisher = {Association for Computing Machinery},
author = {Haro, Antonio and Essa, Irfan and Flickner, Myron},
year = {2000},
keywords = {computer vision, face tracking, gaze tracking, visual tracking},
pages = {167--168},
}
@article{harmon-jones_effect_2008,
title = {The effect of induced compliance on relative left frontal cortical activity: a test of the action-based model of dissonance},
volume = {38},
issn = {1099-0992},
shorttitle = {The effect of induced compliance on relative left frontal cortical activity},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/ejsp.399},
doi = {10.1002/ejsp.399},
abstract = {The action-based model of dissonance and recent advances in neuroscience suggest that commitment to action should cause greater relative left frontal cortical activity. An induced compliance experiment was conducted in which electroencephalographic activity was recorded following commitment to action, operationalized with a perceived choice manipulation. Perceived high as compared to low choice to engage in the counterattitudinal action caused attitudes to be more consistent with the action. Also, high choice caused greater relative left frontal cortical activity than low choice. Copyright © 2006 John Wiley \& Sons, Ltd.},
language = {en},
number = {1},
urldate = {2022-05-10},
journal = {European Journal of Social Psychology},
author = {Harmon-Jones, Eddie and Gerdjikov, Todor and Harmon-Jones, Cindy},
year = {2008},
note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/ejsp.399},
pages = {35--45},
}
@article{popa_reading_2015,
title = {Reading beyond the glance: eye tracking in neurosciences},
volume = {36},
issn = {1590-3478},
shorttitle = {Reading beyond the glance},
url = {https://doi.org/10.1007/s10072-015-2076-6},
doi = {10.1007/s10072-015-2076-6},
abstract = {From an interdisciplinary approach, the neurosciences (NSs) represent the junction of many fields (biology, chemistry, medicine, computer science, and psychology) and aim to explore the structural and functional aspects of the nervous system. Among modern neurophysiological methods that “measure” different processes of the human brain to salience stimuli, a special place belongs to eye tracking (ET). By detecting eye position, gaze direction, sequence of eye movement and visual adaptation during cognitive activities, ET is an effective tool for experimental psychology and neurological research. It provides a quantitative and qualitative analysis of the gaze, which is very useful in understanding choice behavior and perceptual decision making. In the high tech era, ET has several applications related to the interaction between humans and computers. Herein, ET is used to evaluate the spatial orienting of attention, the performance in visual tasks, the reactions to information on websites, the customer response to advertising, and the emotional and cognitive impact of various spurs to the brain.},
language = {en},
number = {5},
urldate = {2022-04-29},
journal = {Neurological Sciences},
author = {Popa, Livia and Selejan, Ovidiu and Scott, Allan and Mureşanu, Dafin F. and Balea, Maria and Rafila, Alexandru},
month = may,
year = {2015},
keywords = {Decision-making, Consumer behavior, Eye tracking (ET), Neurosciences (NSs)},
pages = {683--688},
}
@article{zajonc_social_1965,
title = {Social {Facilitation}},
copyright = {1965 by the American Association for the Advancement of Science},
url = {https://www.science.org/doi/pdf/10.1126/science.149.3681.269},
doi = {10.1126/science.149.3681.269},
language = {EN},
urldate = {2022-05-05},
journal = {Science},
author = {Zajonc, Robert B.},
month = jul,
year = {1965},
note = {Publisher: American Association for the Advancement of Science},
}
@article{jansen_influence_2018,
title = {The {Influence} of the {Presentation} of {Camera} {Surveillance} on {Cheating} and {Pro}-{Social} {Behavior}},
volume = {9},
issn = {1664-1078},
url = {https://www.frontiersin.org/article/10.3389/fpsyg.2018.01937},
abstract = {Introduction: This study is aimed at gaining more insight into the effects of camera-surveillance on behavior. It investigates the effects of three different ways of “framing” camera presence on cheating behavior and pro-social behavior. First, we explore the effect of presenting the camera as the medium through which an intimidating authority watches the participant. Second, we test the effect of presenting the camera as being a neutral, non-intimidating viewer. Third, we investigate the effect of watching oneself via a camera. In contrast to most studies on camera surveillance, we will conduct our experiments in an indoor setting. We also explore possible interaction effects of personality traits; we measured Locus of Control, Need for Approval, Self-Monitoring and Social Value Orientation.Methods: In this experiment participated 86 students, randomly distributed over four conditions: three different ways of framing the camera presence, plus a control condition. Our main dependent variables were various kinds of cheating and pro-social behavior. We established the participant's relevant personality traits using a classification tree.Results: For cheating behavior, findings showed that in the “authorative” way of framing camera presence and in the situation in which participants viewed themselves, participants cheated significantly less compared to a situation without camera-surveillance. We did not find significant effects of camera surveillance on pro-social behavior. Looking at personality traits, we found an indication that people with an internal locus of control are more inclined to cheat when there is no camera present compared to people with an external locus of control. However, the effects of our manipulations were stronger.Conclusion: Our findings support the idea that the framing of a camera's presence does indeed influence cheating behavior, adding to the preventive effects of camera-surveillance. Additionally, this study provides some valuable insights into the influence of camera presence on behavior in general.},
urldate = {2022-04-29},
journal = {Frontiers in Psychology},
author = {Jansen, Anja M. and Giebels, Ellen and van Rompay, Thomas J. L. and Junger, Marianne},
year = {2018},
}
@article{constantinou_effects_2005,
title = {Effects of a {Third} {Party} {Observer} {During} {Neuropsychological} {Assessment}: {When} the {Observer} {Is} a {Video} {Camera}},
volume = {4},
issn = {1521-1029, 1540-7136},
shorttitle = {Effects of a {Third} {Party} {Observer} {During} {Neuropsychological} {Assessment}},
url = {http://www.tandfonline.com/doi/abs/10.1300/J151v04n02_04},
doi = {10.1300/J151v04n02_04},
language = {en},
number = {2},
urldate = {2022-02-28},
journal = {Journal of Forensic Neuropsychology},
author = {Constantinou, Marios and Ashendorf, Lee and McCaffrey, Robert J.},
month = jul,
year = {2005},
pages = {39--47},
}
@article{matthiesen_eye_2013,
title = {Eye tracking, a method for engineering design research on engineers' behavior while analyzing technical systems},
issn = {2220-4334},
url = {https://www.designsociety.org/publication/34592/Eye+tracking%2C+a+method+for+engineering+design+research+on+engineers%27+behavior+while+analyzing+technical+systems},
abstract = {The analysis of technical systems is a central activity in design processes. Engineers need to understand the functions of a system in order to gain inputs for further development. In using design research methods in the area of acquiring functional understanding, data is usually gathered through interviews or observations. Since vision is tightly related to cognition, eye tracking may provide deeper insights into the analyzing behavior of humans. This paper investigates the applicability of different eye tracking technologies for research into function recognition. Pilot studies were conducted to show the practicability of the proposed technologies. In addition to that, the paper introduces relevant analysis methods for raw gaze data. The results suggest that remote and head mounted eye trackers are well suited to observing the behavior of engineers who are analyzing a technical system in different representation forms. Based on these findings, the authors propose the use of eye tracking technologies in qualitative and quantitative empirical studies of how engineers build up understanding of technical systems.},
language = {en},
urldate = {2022-05-04},
journal = {DS 75-7: Proceedings of the 19th International Conference on Engineering Design (ICED13), Design for Harmonies, Vol.7: Human Behaviour in Design, Seoul, Korea, 19-22.08.2013},
author = {Matthiesen, Sven and Meboldt, Mirko and Ruckpaul, Anne and Mussgnug, Moritz},
year = {2013},
note = {ISBN: 9781904670506},
pages = {277--286},
}
@misc{kazdin_single-case_1982,
title = {Single-{Case} {Research} {Designs} - {Methods} for clinical and applied settings},
url = {//global.oup.com/ushe/product/single-case-research-designs-9780190079970},
abstract = {Single-case research has played an important role in developing and evaluating interventions that are designed to alter a particular facet of human functioning. Now thoroughly updated in its third edition, acclaimed author Alan E. Kazdin's Single-Case Research Designs provides a notable contrast to the quantitative methodology approach that pervades the biological and social sciences.},
language = {en},
urldate = {2022-02-28},
journal = {Oxford University Press},
author = {Kazdin, Alan E.},
year = {1982},
note = {Cc: cz
Lang: en
Tab: overview},
}
@misc{kurt_tpack_2018,
title = {{TPACK}: {Technological} {Pedagogical} {Content} {Knowledge} {Framework}},
shorttitle = {{TPACK}},
url = {https://educationaltechnology.net/technological-pedagogical-content-knowledge-tpack-framework/},
abstract = {What is TPACK? Technology has become an increasingly important part of students’ lives beyond school, and even within the classroom it can also help},
language = {en-US},
urldate = {2021-12-07},
journal = {Educational Technology},
author = {Kurt, Serhat},
month = may,
year = {2018},
}
@article{baer_curvilinear_2006,
title = {The curvilinear relation between experienced creative time pressure and creativity: {Moderating} effects of openness to experience and support for creativity.},
volume = {91},
issn = {1939-1854, 0021-9010},
shorttitle = {The curvilinear relation between experienced creative time pressure and creativity},
url = {http://doi.apa.org/getdoi.cfm?doi=10.1037/0021-9010.91.4.963},
doi = {10.1037/0021-9010.91.4.963},
abstract = {This study examined the possibility of a curvilinear relation between the creative time pressure employees experience at work and their creativity. The authors also examined whether this curvilinear relation was moderated by employees’ scores on the openness to experience personality dimension and by the support for creativity employees received from supervisors and coworkers. Data were obtained from 170 employees and 10 supervisors of a manufacturing organization. Results showed an inverted U-shaped creative time pressure-creativity relation for employees who scored high on openness to experience while simultaneously receiving support for creativity. The authors discussed the implications of these results for future research and practice.},
language = {en},
number = {4},
urldate = {2022-05-30},
journal = {Journal of Applied Psychology},
author = {Baer, Markus and Oldham, Greg R.},
year = {2006},
pages = {963--970},
file = {Baer and Oldham - 2006 - The curvilinear relation between experienced creat.pdf:files/7585/Baer and Oldham - 2006 - The curvilinear relation between experienced creat.pdf:application/pdf},
}
@article{khalil_neurocomputational_2022,
title = {A neurocomputational model of creative processes},
volume = {137},
issn = {0149-7634},
url = {https://www.sciencedirect.com/science/article/pii/S0149763422001452},
doi = {10.1016/j.neubiorev.2022.104656},
abstract = {Creativity is associated with finding novel, surprising, and useful solutions. We argue that creative cognitive processes, divergent thinking, abstraction, and improvisation are constructed on different novelty-based processes. The prefrontal cortex plays a role in creative ideation by providing a control mechanism. Moreover, thinking about novel solutions activates the distant or loosely connected neurons of a semantic network that involves the hippocampus. Novelty can also be interpreted as different combinations of earlier learned processes, such as the motor sequencing mechanism of the basal ganglia. In addition, the cerebellum is responsible for the precise control of movements, which is particularly important in improvisation. Our neurocomputational perspective is based on three creative processes centered on novelty seeking, subserved by the prefrontal cortex, hippocampus, cerebellum, basal ganglia, and dopamine. The algorithmic implementation of our model would enable us to describe commonalities and differences between these creative processes based on the proposed neural circuitry. Given that most previous studies have mainly provided theoretical and conceptual models of creativity, this article presents the first brain-inspired neural network model of creative cognition.},
language = {en},
urldate = {2022-06-08},
journal = {Neuroscience \& Biobehavioral Reviews},
author = {Khalil, Radwa and Moustafa, Ahmed A.},
month = jun,
year = {2022},
keywords = {Convergent Thinking, Hippocampus, Prefrontal Cortex, Dopamine, Surprise, Abstraction, Basal Ganglia, Cerebellum, Computational Model, Divergent Thinking, Improvisation, Novelty, Usefulness},
pages = {104656},
}
@book{coste_michel_pdf_nodate,
title = {[{PDF}] {AN} {INTRODUCTION} {TO} {SEMIALGEBRAIC} {GEOMETRY} {\textbar} {Semantic} {Scholar}},
url = {https://www.semanticscholar.org/paper/AN-INTRODUCTION-TO-SEMIALGEBRAIC-GEOMETRY-Coste/77f4f0f1de8e80afc0fe0591ddd4bf3d52098329},
urldate = {2022-07-31},
publisher = {Institut de Recherche Mathématique de Rennes},
author = {Coste, Michel},
}
@book{bochnak_real_2013,
title = {Real {Algebraic} {Geometry}},
isbn = {978-3-662-03718-8},
abstract = {The present volume is a translation, revision and updating of our book (pub lished in French) with the title "Geometrie Algebrique Reelle". Since its pub lication in 1987 the theory has made advances in several directions. There have also been new insights into material already in the French edition. Many of these advances and insights have been incorporated in this English version of the book, so that it may be viewed as being substantially different from the original. We wish to thank Michael Buchner for his careful reading of the text and for his linguistic corrections and stylistic improvements. The initial Jb. TEiX file was prepared by Thierry van Effelterre. The three authors participate in the European research network "Real Algebraic and Analytic Geometry". The first author was partially supported by NATO Collaborative Research Grant 960011. Jacek Bochnak April 1998 Michel Coste Marie-Pranroise Roy Table of Contents Preface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1. Ordered Fields, Real Closed Fields . . . . . . . . . . . . . . . . . . . . . . . 7 1. 1 Ordered Fields, Real Fields . . . . . " . . . . . . . . . . . . . . . . . . . . . . . 7 1. 2 Real Closed Fields. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 1. 3 Real Closure of an Ordered Field. . . . . . . . . . . . . . . . . . . . . . . . . 14 1. 4 The Tarski-Seidenberg Principle. . . . . . . . . . . . . . . . . . . . . . . . . . 17 2. Semi-algebraic Sets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 2. 1 Algebraic and Semi-algebraic Sets. . . . . . . . . . . . . . . . . . . . . . . . 23 2. 2 Projection of Semi-algebraic Sets. Semi-algebraic Mappings. . 26 2. 3 Decomposition of Semi-algebraic Sets. . . . . . . . . . . . . . . . . . . . . 30 2. 4 Connectedness. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 2. 5 Closed and Bounded Semi-algebraic Sets. Curve-selection Lemma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 2. 6 Continuous Semi-algebraic Functions. Lojasiewicz's Inequality 42 2. 7 Separation of Closed Semi-algebraic Sets. . . . . . . . . . . . . . . . . .},
language = {en},
publisher = {Springer Science \& Business Media},
author = {Bochnak, Jacek and Coste, Michel and Roy, Marie-Francoise},
month = nov,
year = {2013},
note = {Google-Books-ID: GJv6CAAAQBAJ},
keywords = {Mathematics / Algebra / General, Mathematics / Geometry / Algebraic},
}
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