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<title>Chapter 6 Conventional genetic programming experiment | Supplemental Material for Directed Digital Evolution Project</title>
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<meta name="twitter:title" content="Chapter 6 Conventional genetic programming experiment | Supplemental Material for Directed Digital Evolution Project" />
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<li><a href="./">Supplemental material</a></li>
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<li class="chapter" data-level="1" data-path="index.html"><a href="index.html"><i class="fa fa-check"></i><b>1</b> Introduction</a><ul>
<li class="chapter" data-level="1.1" data-path="index.html"><a href="index.html#about-this-supplemental-material"><i class="fa fa-check"></i><b>1.1</b> About this supplemental material</a><ul>
<li class="chapter" data-level="1.1.1" data-path="index.html"><a href="index.html#contents"><i class="fa fa-check"></i><b>1.1.1</b> Contents</a></li>
</ul></li>
<li class="chapter" data-level="1.2" data-path="index.html"><a href="index.html#contributing-authors"><i class="fa fa-check"></i><b>1.2</b> Contributing authors</a></li>
<li class="chapter" data-level="1.3" data-path="index.html"><a href="index.html#research-overview"><i class="fa fa-check"></i><b>1.3</b> Research overview</a></li>
</ul></li>
<li class="chapter" data-level="2" data-path="software-availability.html"><a href="software-availability.html"><i class="fa fa-check"></i><b>2</b> Software availability</a></li>
<li class="chapter" data-level="3" data-path="data-availability.html"><a href="data-availability.html"><i class="fa fa-check"></i><b>3</b> Data availability</a></li>
<li class="chapter" data-level="4" data-path="compiling-and-running-our-experiments.html"><a href="compiling-and-running-our-experiments.html"><i class="fa fa-check"></i><b>4</b> Compiling and running our experiments</a><ul>
<li class="chapter" data-level="4.1" data-path="compiling-and-running-our-experiments.html"><a href="compiling-and-running-our-experiments.html#manual"><i class="fa fa-check"></i><b>4.1</b> Manual</a></li>
<li class="chapter" data-level="4.2" data-path="compiling-and-running-our-experiments.html"><a href="compiling-and-running-our-experiments.html#docker"><i class="fa fa-check"></i><b>4.2</b> Docker</a></li>
</ul></li>
<li class="chapter" data-level="5" data-path="digital-organisms.html"><a href="digital-organisms.html"><i class="fa fa-check"></i><b>5</b> Digital Organisms</a><ul>
<li class="chapter" data-level="5.1" data-path="digital-organisms.html"><a href="digital-organisms.html#virtual-hardware-components"><i class="fa fa-check"></i><b>5.1</b> Virtual Hardware Components</a></li>
<li class="chapter" data-level="5.2" data-path="digital-organisms.html"><a href="digital-organisms.html#instruction-set"><i class="fa fa-check"></i><b>5.2</b> Instruction set</a></li>
<li class="chapter" data-level="5.3" data-path="digital-organisms.html"><a href="digital-organisms.html#ancestral-genomes"><i class="fa fa-check"></i><b>5.3</b> Ancestral genomes</a><ul>
<li class="chapter" data-level="5.3.1" data-path="digital-organisms.html"><a href="digital-organisms.html#ancestral-genome-for-genetic-programming-experiment"><i class="fa fa-check"></i><b>5.3.1</b> Ancestral genome for genetic programming experiment</a></li>
<li class="chapter" data-level="5.3.2" data-path="digital-organisms.html"><a href="digital-organisms.html#ancestral-genome-for-directed-evolution-experiments"><i class="fa fa-check"></i><b>5.3.2</b> Ancestral genome for directed evolution experiments</a></li>
</ul></li>
</ul></li>
<li class="chapter" data-level="6" data-path="conventional-genetic-programming-experiment.html"><a href="conventional-genetic-programming-experiment.html"><i class="fa fa-check"></i><b>6</b> Conventional genetic programming experiment</a><ul>
<li class="chapter" data-level="6.1" data-path="conventional-genetic-programming-experiment.html"><a href="conventional-genetic-programming-experiment.html#overview"><i class="fa fa-check"></i><b>6.1</b> Overview</a></li>
<li class="chapter" data-level="6.2" data-path="conventional-genetic-programming-experiment.html"><a href="conventional-genetic-programming-experiment.html#analysis-dependencies"><i class="fa fa-check"></i><b>6.2</b> Analysis dependencies</a></li>
<li class="chapter" data-level="6.3" data-path="conventional-genetic-programming-experiment.html"><a href="conventional-genetic-programming-experiment.html#setup"><i class="fa fa-check"></i><b>6.3</b> Setup</a></li>
<li class="chapter" data-level="6.4" data-path="conventional-genetic-programming-experiment.html"><a href="conventional-genetic-programming-experiment.html#number-of-successful-replicates"><i class="fa fa-check"></i><b>6.4</b> Number of successful replicates</a></li>
<li class="chapter" data-level="6.5" data-path="conventional-genetic-programming-experiment.html"><a href="conventional-genetic-programming-experiment.html#final-task-coverage"><i class="fa fa-check"></i><b>6.5</b> Final task coverage</a></li>
<li class="chapter" data-level="6.6" data-path="conventional-genetic-programming-experiment.html"><a href="conventional-genetic-programming-experiment.html#generation-2000-task-coverage"><i class="fa fa-check"></i><b>6.6</b> Generation 2,000 task coverage</a></li>
<li class="chapter" data-level="6.7" data-path="conventional-genetic-programming-experiment.html"><a href="conventional-genetic-programming-experiment.html#population-level-task-coverage"><i class="fa fa-check"></i><b>6.7</b> Population-level task coverage</a></li>
<li class="chapter" data-level="6.8" data-path="conventional-genetic-programming-experiment.html"><a href="conventional-genetic-programming-experiment.html#generations-elapsed-before-a-solution-evolves"><i class="fa fa-check"></i><b>6.8</b> Generations elapsed before a solution evolves</a></li>
<li class="chapter" data-level="6.9" data-path="conventional-genetic-programming-experiment.html"><a href="conventional-genetic-programming-experiment.html#best-task-coverage-over-time"><i class="fa fa-check"></i><b>6.9</b> Best task coverage over time</a></li>
<li class="chapter" data-level="6.10" data-path="conventional-genetic-programming-experiment.html"><a href="conventional-genetic-programming-experiment.html#manuscript-figure"><i class="fa fa-check"></i><b>6.10</b> Manuscript Figure</a></li>
</ul></li>
<li class="chapter" data-level="7" data-path="directed-digital-evolution-experiment.html"><a href="directed-digital-evolution-experiment.html"><i class="fa fa-check"></i><b>7</b> Directed digital evolution experiment</a><ul>
<li class="chapter" data-level="7.1" data-path="directed-digital-evolution-experiment.html"><a href="directed-digital-evolution-experiment.html#overview-1"><i class="fa fa-check"></i><b>7.1</b> Overview</a></li>
<li class="chapter" data-level="7.2" data-path="directed-digital-evolution-experiment.html"><a href="directed-digital-evolution-experiment.html#analysis-dependencies-1"><i class="fa fa-check"></i><b>7.2</b> Analysis dependencies</a></li>
<li class="chapter" data-level="7.3" data-path="directed-digital-evolution-experiment.html"><a href="directed-digital-evolution-experiment.html#setup-1"><i class="fa fa-check"></i><b>7.3</b> Setup</a></li>
<li class="chapter" data-level="7.4" data-path="directed-digital-evolution-experiment.html"><a href="directed-digital-evolution-experiment.html#best-single-population-task-coverage"><i class="fa fa-check"></i><b>7.4</b> Best single-population task coverage</a><ul>
<li class="chapter" data-level="7.4.1" data-path="directed-digital-evolution-experiment.html"><a href="directed-digital-evolution-experiment.html#best-single-population-task-coverage-time-series"><i class="fa fa-check"></i><b>7.4.1</b> Best single-population task coverage time series</a></li>
</ul></li>
<li class="chapter" data-level="7.5" data-path="directed-digital-evolution-experiment.html"><a href="directed-digital-evolution-experiment.html#metapopulation-task-coverage"><i class="fa fa-check"></i><b>7.5</b> Metapopulation task coverage</a><ul>
<li class="chapter" data-level="7.5.1" data-path="directed-digital-evolution-experiment.html"><a href="directed-digital-evolution-experiment.html#metapopulation-task-coverage-time-series"><i class="fa fa-check"></i><b>7.5.1</b> Metapopulation task coverage time series</a></li>
</ul></li>
<li class="chapter" data-level="7.6" data-path="directed-digital-evolution-experiment.html"><a href="directed-digital-evolution-experiment.html#metapopulation-task-profile-diversity"><i class="fa fa-check"></i><b>7.6</b> Metapopulation task profile diversity</a><ul>
<li class="chapter" data-level="7.6.1" data-path="directed-digital-evolution-experiment.html"><a href="directed-digital-evolution-experiment.html#number-of-different-task-profiles"><i class="fa fa-check"></i><b>7.6.1</b> Number of different task profiles</a></li>
<li class="chapter" data-level="7.6.2" data-path="directed-digital-evolution-experiment.html"><a href="directed-digital-evolution-experiment.html#task-profile-spread"><i class="fa fa-check"></i><b>7.6.2</b> Task profile spread</a></li>
<li class="chapter" data-level="7.6.3" data-path="directed-digital-evolution-experiment.html"><a href="directed-digital-evolution-experiment.html#task-profile-entropy"><i class="fa fa-check"></i><b>7.6.3</b> Task profile entropy</a></li>
</ul></li>
<li class="chapter" data-level="7.7" data-path="directed-digital-evolution-experiment.html"><a href="directed-digital-evolution-experiment.html#task-coverage-per-n-populations"><i class="fa fa-check"></i><b>7.7</b> Task coverage per N populations</a></li>
<li class="chapter" data-level="7.8" data-path="directed-digital-evolution-experiment.html"><a href="directed-digital-evolution-experiment.html#average-number-of-different-populations-selected-per-generation"><i class="fa fa-check"></i><b>7.8</b> Average number of different populations selected per generation</a><ul>
<li class="chapter" data-level="7.8.1" data-path="directed-digital-evolution-experiment.html"><a href="directed-digital-evolution-experiment.html#entropy-of-selected-population-ids"><i class="fa fa-check"></i><b>7.8.1</b> Entropy of selected population IDs</a></li>
</ul></li>
<li class="chapter" data-level="7.9" data-path="directed-digital-evolution-experiment.html"><a href="directed-digital-evolution-experiment.html#average-number-of-organisms-in-populations-at-end-of-maturation-period"><i class="fa fa-check"></i><b>7.9</b> Average number of organisms in populations at end of maturation period</a></li>
<li class="chapter" data-level="7.10" data-path="directed-digital-evolution-experiment.html"><a href="directed-digital-evolution-experiment.html#average-generations-per-maturation-period"><i class="fa fa-check"></i><b>7.10</b> Average generations per maturation period</a></li>
<li class="chapter" data-level="7.11" data-path="directed-digital-evolution-experiment.html"><a href="directed-digital-evolution-experiment.html#representative-task-profiles"><i class="fa fa-check"></i><b>7.11</b> Representative task profiles</a></li>
<li class="chapter" data-level="7.12" data-path="directed-digital-evolution-experiment.html"><a href="directed-digital-evolution-experiment.html#manuscript-figures"><i class="fa fa-check"></i><b>7.12</b> Manuscript figures</a></li>
</ul></li>
<li class="chapter" data-level="8" data-path="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html"><a href="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html"><i class="fa fa-check"></i><b>8</b> Aligned individual-level and population-level task directed evolution experiment</a><ul>
<li class="chapter" data-level="8.1" data-path="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html"><a href="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html#overview-2"><i class="fa fa-check"></i><b>8.1</b> Overview</a></li>
<li class="chapter" data-level="8.2" data-path="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html"><a href="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html#analysis-dependencies-2"><i class="fa fa-check"></i><b>8.2</b> Analysis dependencies</a></li>
<li class="chapter" data-level="8.3" data-path="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html"><a href="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html#setup-2"><i class="fa fa-check"></i><b>8.3</b> Setup</a></li>
<li class="chapter" data-level="8.4" data-path="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html"><a href="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html#best-single-population-task-coverage-1"><i class="fa fa-check"></i><b>8.4</b> Best single-population task coverage</a><ul>
<li class="chapter" data-level="8.4.1" data-path="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html"><a href="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html#best-single-population-task-coverage-time-series-1"><i class="fa fa-check"></i><b>8.4.1</b> Best single-population task coverage time series</a></li>
</ul></li>
<li class="chapter" data-level="8.5" data-path="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html"><a href="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html#metapopulation-task-coverage-1"><i class="fa fa-check"></i><b>8.5</b> Metapopulation task coverage</a><ul>
<li class="chapter" data-level="8.5.1" data-path="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html"><a href="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html#metapopulation-task-coverage-time-series-1"><i class="fa fa-check"></i><b>8.5.1</b> Metapopulation task coverage time series</a></li>
</ul></li>
<li class="chapter" data-level="8.6" data-path="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html"><a href="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html#metapopulation-task-profile-diversity-1"><i class="fa fa-check"></i><b>8.6</b> Metapopulation task profile diversity</a><ul>
<li class="chapter" data-level="8.6.1" data-path="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html"><a href="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html#number-of-different-task-profiles-1"><i class="fa fa-check"></i><b>8.6.1</b> Number of different task profiles</a></li>
<li class="chapter" data-level="8.6.2" data-path="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html"><a href="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html#task-profile-spread-1"><i class="fa fa-check"></i><b>8.6.2</b> Task profile spread</a></li>
<li class="chapter" data-level="8.6.3" data-path="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html"><a href="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html#task-profile-entropy-1"><i class="fa fa-check"></i><b>8.6.3</b> Task profile entropy</a></li>
</ul></li>
<li class="chapter" data-level="8.7" data-path="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html"><a href="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html#task-coverage-per-n-populations-1"><i class="fa fa-check"></i><b>8.7</b> Task coverage per N populations</a></li>
<li class="chapter" data-level="8.8" data-path="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html"><a href="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html#average-number-of-different-populations-selected-per-generation-1"><i class="fa fa-check"></i><b>8.8</b> Average number of different populations selected per generation</a><ul>
<li class="chapter" data-level="8.8.1" data-path="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html"><a href="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html#entropy-of-selected-population-ids-1"><i class="fa fa-check"></i><b>8.8.1</b> Entropy of selected population IDs</a></li>
</ul></li>
<li class="chapter" data-level="8.9" data-path="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html"><a href="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html#average-number-of-organisms-in-populations-at-end-of-maturation-period-1"><i class="fa fa-check"></i><b>8.9</b> Average number of organisms in populations at end of maturation period</a></li>
<li class="chapter" data-level="8.10" data-path="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html"><a href="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html#average-generations-per-maturation-period-1"><i class="fa fa-check"></i><b>8.10</b> Average generations per maturation period</a></li>
<li class="chapter" data-level="8.11" data-path="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html"><a href="aligned-individual-level-and-population-level-task-directed-evolution-experiment.html#manuscript-figures-1"><i class="fa fa-check"></i><b>8.11</b> Manuscript figures</a></li>
</ul></li>
<li class="chapter" data-level="9" data-path="varying-population-maturation-period.html"><a href="varying-population-maturation-period.html"><i class="fa fa-check"></i><b>9</b> Varying population maturation period</a><ul>
<li class="chapter" data-level="9.1" data-path="varying-population-maturation-period.html"><a href="varying-population-maturation-period.html#overview-3"><i class="fa fa-check"></i><b>9.1</b> Overview</a></li>
<li class="chapter" data-level="9.2" data-path="varying-population-maturation-period.html"><a href="varying-population-maturation-period.html#analysis-dependencies-3"><i class="fa fa-check"></i><b>9.2</b> Analysis dependencies</a></li>
<li class="chapter" data-level="9.3" data-path="varying-population-maturation-period.html"><a href="varying-population-maturation-period.html#setup-3"><i class="fa fa-check"></i><b>9.3</b> Setup</a></li>
<li class="chapter" data-level="9.4" data-path="varying-population-maturation-period.html"><a href="varying-population-maturation-period.html#average-number-of-organisms"><i class="fa fa-check"></i><b>9.4</b> Average number of organisms</a></li>
<li class="chapter" data-level="9.5" data-path="varying-population-maturation-period.html"><a href="varying-population-maturation-period.html#average-generations-elapsed-during-the-maturation-period"><i class="fa fa-check"></i><b>9.5</b> Average generations elapsed during the maturation period</a></li>
<li class="chapter" data-level="9.6" data-path="varying-population-maturation-period.html"><a href="varying-population-maturation-period.html#total-generations"><i class="fa fa-check"></i><b>9.6</b> Total generations</a></li>
<li class="chapter" data-level="9.7" data-path="varying-population-maturation-period.html"><a href="varying-population-maturation-period.html#performance"><i class="fa fa-check"></i><b>9.7</b> Performance</a><ul>
<li class="chapter" data-level="9.7.1" data-path="varying-population-maturation-period.html"><a href="varying-population-maturation-period.html#cpu-cycles-per-replication"><i class="fa fa-check"></i><b>9.7.1</b> CPU cycles per replication</a></li>
<li class="chapter" data-level="9.7.2" data-path="varying-population-maturation-period.html"><a href="varying-population-maturation-period.html#best-population-task-coverage"><i class="fa fa-check"></i><b>9.7.2</b> Best-population task coverage</a></li>
<li class="chapter" data-level="9.7.3" data-path="varying-population-maturation-period.html"><a href="varying-population-maturation-period.html#metapopulation-task-coverage-2"><i class="fa fa-check"></i><b>9.7.3</b> Metapopulation task coverage</a></li>
</ul></li>
<li class="chapter" data-level="9.8" data-path="varying-population-maturation-period.html"><a href="varying-population-maturation-period.html#population-level-task-profile-diversity"><i class="fa fa-check"></i><b>9.8</b> Population-level Task Profile Diversity</a><ul>
<li class="chapter" data-level="9.8.1" data-path="varying-population-maturation-period.html"><a href="varying-population-maturation-period.html#task-profile-richness"><i class="fa fa-check"></i><b>9.8.1</b> Task profile richness</a></li>
<li class="chapter" data-level="9.8.2" data-path="varying-population-maturation-period.html"><a href="varying-population-maturation-period.html#task-profile-entropy-2"><i class="fa fa-check"></i><b>9.8.2</b> Task profile entropy</a></li>
<li class="chapter" data-level="9.8.3" data-path="varying-population-maturation-period.html"><a href="varying-population-maturation-period.html#spread-average-cosine-distance"><i class="fa fa-check"></i><b>9.8.3</b> Spread (average cosine distance)</a></li>
</ul></li>
<li class="chapter" data-level="9.9" data-path="varying-population-maturation-period.html"><a href="varying-population-maturation-period.html#selection"><i class="fa fa-check"></i><b>9.9</b> Selection</a><ul>
<li class="chapter" data-level="9.9.1" data-path="varying-population-maturation-period.html"><a href="varying-population-maturation-period.html#average-number-of-unique-populations-selected"><i class="fa fa-check"></i><b>9.9.1</b> Average number of unique populations selected</a></li>
<li class="chapter" data-level="9.9.2" data-path="varying-population-maturation-period.html"><a href="varying-population-maturation-period.html#average-entropy-of-selection-ids"><i class="fa fa-check"></i><b>9.9.2</b> Average entropy of selection ids</a></li>
</ul></li>
<li class="chapter" data-level="9.10" data-path="varying-population-maturation-period.html"><a href="varying-population-maturation-period.html#manuscript-figures-2"><i class="fa fa-check"></i><b>9.10</b> Manuscript Figures</a></li>
<li class="chapter" data-level="9.11" data-path="varying-population-maturation-period.html"><a href="varying-population-maturation-period.html#discussion"><i class="fa fa-check"></i><b>9.11</b> Discussion</a></li>
</ul></li>
<li class="chapter" data-level="10" data-path="varied-genome-lengths.html"><a href="varied-genome-lengths.html"><i class="fa fa-check"></i><b>10</b> Varied genome lengths</a><ul>
<li class="chapter" data-level="10.1" data-path="varied-genome-lengths.html"><a href="varied-genome-lengths.html#overview-4"><i class="fa fa-check"></i><b>10.1</b> Overview</a></li>
<li class="chapter" data-level="10.2" data-path="varied-genome-lengths.html"><a href="varied-genome-lengths.html#analysis-dependencies-4"><i class="fa fa-check"></i><b>10.2</b> Analysis dependencies</a></li>
<li class="chapter" data-level="10.3" data-path="varied-genome-lengths.html"><a href="varied-genome-lengths.html#setup-4"><i class="fa fa-check"></i><b>10.3</b> Setup</a></li>
<li class="chapter" data-level="10.4" data-path="varied-genome-lengths.html"><a href="varied-genome-lengths.html#average-generations-per-maturation-period-2"><i class="fa fa-check"></i><b>10.4</b> Average generations per maturation period</a></li>
<li class="chapter" data-level="10.5" data-path="varied-genome-lengths.html"><a href="varied-genome-lengths.html#total-generations-over-experiment"><i class="fa fa-check"></i><b>10.5</b> Total generations over experiment</a></li>
<li class="chapter" data-level="10.6" data-path="varied-genome-lengths.html"><a href="varied-genome-lengths.html#performance-1"><i class="fa fa-check"></i><b>10.6</b> Performance</a><ul>
<li class="chapter" data-level="10.6.1" data-path="varied-genome-lengths.html"><a href="varied-genome-lengths.html#cpu-cycles-per-replication-1"><i class="fa fa-check"></i><b>10.6.1</b> CPU cycles per replication</a></li>
<li class="chapter" data-level="10.6.2" data-path="varied-genome-lengths.html"><a href="varied-genome-lengths.html#best-single-population-task-coverage-2"><i class="fa fa-check"></i><b>10.6.2</b> Best single-population task coverage</a></li>
<li class="chapter" data-level="10.6.3" data-path="varied-genome-lengths.html"><a href="varied-genome-lengths.html#metapopulation-task-coverage-3"><i class="fa fa-check"></i><b>10.6.3</b> Metapopulation task coverage</a></li>
</ul></li>
<li class="chapter" data-level="10.7" data-path="varied-genome-lengths.html"><a href="varied-genome-lengths.html#population-level-task-profile-diversity-1"><i class="fa fa-check"></i><b>10.7</b> Population-level task profile diversity</a><ul>
<li class="chapter" data-level="10.7.1" data-path="varied-genome-lengths.html"><a href="varied-genome-lengths.html#task-profile-richness-1"><i class="fa fa-check"></i><b>10.7.1</b> Task profile richness</a></li>
<li class="chapter" data-level="10.7.2" data-path="varied-genome-lengths.html"><a href="varied-genome-lengths.html#task-profile-entropy-3"><i class="fa fa-check"></i><b>10.7.2</b> Task profile entropy</a></li>
<li class="chapter" data-level="10.7.3" data-path="varied-genome-lengths.html"><a href="varied-genome-lengths.html#spread-avg-cosine-distance"><i class="fa fa-check"></i><b>10.7.3</b> Spread (avg cosine distance)</a></li>
</ul></li>
<li class="chapter" data-level="10.8" data-path="varied-genome-lengths.html"><a href="varied-genome-lengths.html#selection-1"><i class="fa fa-check"></i><b>10.8</b> Selection</a><ul>
<li class="chapter" data-level="10.8.1" data-path="varied-genome-lengths.html"><a href="varied-genome-lengths.html#average-number-of-unique-populations-selected-1"><i class="fa fa-check"></i><b>10.8.1</b> Average number of unique populations selected</a></li>
<li class="chapter" data-level="10.8.2" data-path="varied-genome-lengths.html"><a href="varied-genome-lengths.html#average-entropy-of-selection-ids-1"><i class="fa fa-check"></i><b>10.8.2</b> Average entropy of selection ids</a></li>
</ul></li>
<li class="chapter" data-level="10.9" data-path="varied-genome-lengths.html"><a href="varied-genome-lengths.html#discussion-1"><i class="fa fa-check"></i><b>10.9</b> Discussion</a></li>
</ul></li>
<li class="chapter" data-level="11" data-path="population-propagule-sample-size.html"><a href="population-propagule-sample-size.html"><i class="fa fa-check"></i><b>11</b> Population propagule sample size</a><ul>
<li class="chapter" data-level="11.1" data-path="population-propagule-sample-size.html"><a href="population-propagule-sample-size.html#overview-5"><i class="fa fa-check"></i><b>11.1</b> Overview</a></li>
<li class="chapter" data-level="11.2" data-path="population-propagule-sample-size.html"><a href="population-propagule-sample-size.html#analysis-dependencies-5"><i class="fa fa-check"></i><b>11.2</b> Analysis dependencies</a></li>
<li class="chapter" data-level="11.3" data-path="population-propagule-sample-size.html"><a href="population-propagule-sample-size.html#setup-5"><i class="fa fa-check"></i><b>11.3</b> Setup</a></li>
<li class="chapter" data-level="11.4" data-path="population-propagule-sample-size.html"><a href="population-propagule-sample-size.html#average-number-of-organisms-1"><i class="fa fa-check"></i><b>11.4</b> Average number of organisms</a></li>
<li class="chapter" data-level="11.5" data-path="population-propagule-sample-size.html"><a href="population-propagule-sample-size.html#average-generations-per-maturation-period-3"><i class="fa fa-check"></i><b>11.5</b> Average generations per maturation period</a></li>
<li class="chapter" data-level="11.6" data-path="population-propagule-sample-size.html"><a href="population-propagule-sample-size.html#performance-2"><i class="fa fa-check"></i><b>11.6</b> Performance</a><ul>
<li class="chapter" data-level="11.6.1" data-path="population-propagule-sample-size.html"><a href="population-propagule-sample-size.html#best-population-task-coverage-1"><i class="fa fa-check"></i><b>11.6.1</b> Best population task coverage</a></li>
<li class="chapter" data-level="11.6.2" data-path="population-propagule-sample-size.html"><a href="population-propagule-sample-size.html#metapopulation-task-coverage-4"><i class="fa fa-check"></i><b>11.6.2</b> Metapopulation task coverage</a></li>
</ul></li>
</ul></li>
<li class="chapter" data-level="" data-path="references.html"><a href="references.html"><i class="fa fa-check"></i>References</a></li>
<li class="divider"></li>
<li><a href="https://github.com/rstudio/bookdown" target="blank">Published with ❤ and bookdown</a></li>
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<i class="fa fa-circle-o-notch fa-spin"></i><a href="./">Supplemental Material for Directed Digital Evolution Project</a>
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<div id="conventional-genetic-programming-experiment" class="section level1 hasAnchor">
<h1><span class="header-section-number">Chapter 6</span> Conventional genetic programming experiment<a href="conventional-genetic-programming-experiment.html#conventional-genetic-programming-experiment" class="anchor-section" aria-label="Anchor link to header"></a></h1>
<p>Data analyses for our conventional evolutionary computing experiment.</p>
<div id="overview" class="section level2 hasAnchor">
<h2><span class="header-section-number">6.1</span> Overview<a href="conventional-genetic-programming-experiment.html#overview" class="anchor-section" aria-label="Anchor link to header"></a></h2>
<div class="sourceCode" id="cb8"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb8-1" title="1">experiment_slug <-<span class="st"> "2021-11-15-ec"</span></a>
<a class="sourceLine" id="cb8-2" title="2"></a>
<a class="sourceLine" id="cb8-3" title="3">working_directory <-<span class="st"> </span><span class="kw">paste0</span>(<span class="st">"experiments/"</span>,experiment_slug,<span class="st">"/analysis/"</span>)</a></code></pre></div>
</div>
<div id="analysis-dependencies" class="section level2 hasAnchor">
<h2><span class="header-section-number">6.2</span> Analysis dependencies<a href="conventional-genetic-programming-experiment.html#analysis-dependencies" class="anchor-section" aria-label="Anchor link to header"></a></h2>
<p>Load all required R libraries</p>
<div class="sourceCode" id="cb9"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb9-1" title="1"><span class="kw">library</span>(tidyverse)</a></code></pre></div>
<pre><code>## -- Attaching packages --------------------------------------- tidyverse 1.3.1 --</code></pre>
<pre><code>## v ggplot2 3.3.6 v purrr 0.3.4
## v tibble 3.1.7 v dplyr 1.0.9
## v tidyr 1.2.0 v stringr 1.4.0
## v readr 2.1.2 v forcats 0.5.1</code></pre>
<pre><code>## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()</code></pre>
<div class="sourceCode" id="cb13"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb13-1" title="1"><span class="kw">library</span>(ggplot2)</a>
<a class="sourceLine" id="cb13-2" title="2"><span class="kw">library</span>(cowplot)</a>
<a class="sourceLine" id="cb13-3" title="3"><span class="kw">library</span>(RColorBrewer)</a>
<a class="sourceLine" id="cb13-4" title="4"><span class="kw">library</span>(khroma)</a>
<a class="sourceLine" id="cb13-5" title="5"><span class="kw">source</span>(<span class="st">"https://gist.githubusercontent.com/benmarwick/2a1bb0133ff568cbe28d/raw/fb53bd97121f7f9ce947837ef1a4c65a73bffb3f/geom_flat_violin.R"</span>)</a></code></pre></div>
<p>These analyses were knit with the following environment:</p>
<div class="sourceCode" id="cb14"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb14-1" title="1"><span class="kw">print</span>(version)</a></code></pre></div>
<pre><code>## _
## platform x86_64-pc-linux-gnu
## arch x86_64
## os linux-gnu
## system x86_64, linux-gnu
## status
## major 4
## minor 2.1
## year 2022
## month 06
## day 23
## svn rev 82513
## language R
## version.string R version 4.2.1 (2022-06-23)
## nickname Funny-Looking Kid</code></pre>
</div>
<div id="setup" class="section level2 hasAnchor">
<h2><span class="header-section-number">6.3</span> Setup<a href="conventional-genetic-programming-experiment.html#setup" class="anchor-section" aria-label="Anchor link to header"></a></h2>
<p>Load experiment summary data.</p>
<div class="sourceCode" id="cb16"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb16-1" title="1">exp_summary_data_loc <-<span class="st"> </span><span class="kw">paste0</span>(working_directory,<span class="st">"data/experiment_summary.csv"</span>)</a>
<a class="sourceLine" id="cb16-2" title="2">exp_summary_data <-<span class="st"> </span><span class="kw">read.csv</span>(exp_summary_data_loc, <span class="dt">na.strings=</span><span class="st">"NONE"</span>)</a>
<a class="sourceLine" id="cb16-3" title="3"></a>
<a class="sourceLine" id="cb16-4" title="4">exp_summary_data<span class="op">$</span>SELECTION_METHOD <-<span class="st"> </span><span class="kw">factor</span>(</a>
<a class="sourceLine" id="cb16-5" title="5"> exp_summary_data<span class="op">$</span>SELECTION_METHOD,</a>
<a class="sourceLine" id="cb16-6" title="6"> <span class="dt">levels=</span><span class="kw">c</span>(</a>
<a class="sourceLine" id="cb16-7" title="7"> <span class="st">"elite"</span>,</a>
<a class="sourceLine" id="cb16-8" title="8"> <span class="st">"elite-10"</span>,</a>
<a class="sourceLine" id="cb16-9" title="9"> <span class="st">"tournament"</span>,</a>
<a class="sourceLine" id="cb16-10" title="10"> <span class="st">"lexicase"</span>,</a>
<a class="sourceLine" id="cb16-11" title="11"> <span class="st">"non-dominated-elite"</span>,</a>
<a class="sourceLine" id="cb16-12" title="12"> <span class="st">"non-dominated-tournament"</span>,</a>
<a class="sourceLine" id="cb16-13" title="13"> <span class="st">"random"</span>,</a>
<a class="sourceLine" id="cb16-14" title="14"> <span class="st">"none"</span></a>
<a class="sourceLine" id="cb16-15" title="15"> ),</a>
<a class="sourceLine" id="cb16-16" title="16"> <span class="dt">labels=</span><span class="kw">c</span>(</a>
<a class="sourceLine" id="cb16-17" title="17"> <span class="st">"elite"</span>,</a>
<a class="sourceLine" id="cb16-18" title="18"> <span class="st">"elite-10"</span>,</a>
<a class="sourceLine" id="cb16-19" title="19"> <span class="st">"tourn"</span>,</a>
<a class="sourceLine" id="cb16-20" title="20"> <span class="st">"lex"</span>,</a>
<a class="sourceLine" id="cb16-21" title="21"> <span class="st">"nde"</span>,</a>
<a class="sourceLine" id="cb16-22" title="22"> <span class="st">"ndt"</span>,</a>
<a class="sourceLine" id="cb16-23" title="23"> <span class="st">"random"</span>,</a>
<a class="sourceLine" id="cb16-24" title="24"> <span class="st">"none"</span></a>
<a class="sourceLine" id="cb16-25" title="25"> )</a>
<a class="sourceLine" id="cb16-26" title="26">)</a></code></pre></div>
<p>Load time series data.</p>
<div class="sourceCode" id="cb17"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb17-1" title="1">time_series_data_loc <-<span class="st"> </span><span class="kw">paste0</span>(working_directory,<span class="st">"data/pop_snapshot_time_series_corrected.csv"</span>)</a>
<a class="sourceLine" id="cb17-2" title="2">time_series_data <-<span class="st"> </span><span class="kw">read.csv</span>(time_series_data_loc, <span class="dt">na.strings=</span><span class="st">"NONE"</span>)</a>
<a class="sourceLine" id="cb17-3" title="3"></a>
<a class="sourceLine" id="cb17-4" title="4">get_sel <-<span class="st"> </span><span class="cf">function</span>(seed) {</a>
<a class="sourceLine" id="cb17-5" title="5"> <span class="kw">return</span>(<span class="kw">filter</span>(exp_summary_data, SEED<span class="op">==</span>seed)<span class="op">$</span>SELECTION_METHOD)</a>
<a class="sourceLine" id="cb17-6" title="6">}</a>
<a class="sourceLine" id="cb17-7" title="7"></a>
<a class="sourceLine" id="cb17-8" title="8">solution_evolved_fun <-<span class="st"> </span><span class="cf">function</span>(seed, update) {</a>
<a class="sourceLine" id="cb17-9" title="9"> d <-<span class="st"> </span><span class="kw">filter</span>(exp_summary_data, SEED<span class="op">==</span>seed)</a>
<a class="sourceLine" id="cb17-10" title="10"> <span class="kw">return</span>(update<span class="op">==</span>d<span class="op">$</span>update <span class="op">&&</span><span class="st"> </span>d<span class="op">$</span>max_fit_is_solution<span class="op">==</span><span class="st">"1"</span>);</a>
<a class="sourceLine" id="cb17-11" title="11">}</a>
<a class="sourceLine" id="cb17-12" title="12"></a>
<a class="sourceLine" id="cb17-13" title="13">time_series_data<span class="op">$</span>SELECTION_METHOD <-<span class="st"> </span><span class="kw">mapply</span>(</a>
<a class="sourceLine" id="cb17-14" title="14"> get_sel,</a>
<a class="sourceLine" id="cb17-15" title="15"> time_series_data<span class="op">$</span>SEED</a>
<a class="sourceLine" id="cb17-16" title="16">)</a>
<a class="sourceLine" id="cb17-17" title="17"></a>
<a class="sourceLine" id="cb17-18" title="18">time_series_data<span class="op">$</span>solution_evolved <-<span class="st"> </span><span class="kw">mapply</span>(</a>
<a class="sourceLine" id="cb17-19" title="19"> solution_evolved_fun,</a>
<a class="sourceLine" id="cb17-20" title="20"> time_series_data<span class="op">$</span>SEED,</a>
<a class="sourceLine" id="cb17-21" title="21"> time_series_data<span class="op">$</span>update</a>
<a class="sourceLine" id="cb17-22" title="22">)</a>
<a class="sourceLine" id="cb17-23" title="23"></a>
<a class="sourceLine" id="cb17-24" title="24">time_series_data<span class="op">$</span>SELECTION_METHOD <-<span class="st"> </span><span class="kw">as.factor</span>(</a>
<a class="sourceLine" id="cb17-25" title="25"> time_series_data<span class="op">$</span>SELECTION_METHOD</a>
<a class="sourceLine" id="cb17-26" title="26">)</a>
<a class="sourceLine" id="cb17-27" title="27"></a>
<a class="sourceLine" id="cb17-28" title="28">exp_data_gen_<span class="dv">2000</span> <-<span class="st"> </span><span class="kw">filter</span>(time_series_data, update<span class="op">==</span><span class="dv">2000</span>)</a></code></pre></div>
<p>Miscellaneous setup.</p>
<div class="sourceCode" id="cb18"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb18-1" title="1"><span class="co"># Configure our default graphing theme</span></a>
<a class="sourceLine" id="cb18-2" title="2"><span class="kw">theme_set</span>(<span class="kw">theme_cowplot</span>())</a>
<a class="sourceLine" id="cb18-3" title="3"><span class="co"># Palette</span></a>
<a class="sourceLine" id="cb18-4" title="4">scale_fill_fun <-<span class="st"> </span>scale_fill_bright</a>
<a class="sourceLine" id="cb18-5" title="5">scale_color_fun <-<span class="st"> </span>scale_color_bright</a>
<a class="sourceLine" id="cb18-6" title="6"><span class="co"># Create a directory to store plots</span></a>
<a class="sourceLine" id="cb18-7" title="7">plot_directory <-<span class="st"> </span><span class="kw">paste0</span>(working_directory, <span class="st">"plots/"</span>)</a>
<a class="sourceLine" id="cb18-8" title="8"><span class="kw">dir.create</span>(plot_directory, <span class="dt">showWarnings=</span><span class="ot">FALSE</span>)</a>
<a class="sourceLine" id="cb18-9" title="9"><span class="co"># Order selection schemes.</span></a>
<a class="sourceLine" id="cb18-10" title="10">selection_method_breaks <-<span class="st"> </span><span class="kw">c</span>(<span class="st">"elite"</span>, <span class="st">"elite-10"</span>, <span class="st">"tourn"</span>, <span class="st">"lex"</span>, <span class="st">"nde"</span>, <span class="st">"random"</span>, <span class="st">"none"</span>)</a>
<a class="sourceLine" id="cb18-11" title="11">selection_method_labels <-<span class="st"> </span><span class="kw">c</span>(<span class="st">"ELITE"</span>, <span class="st">"TOP-10"</span>, <span class="st">"TOURN"</span>, <span class="st">"LEX"</span>, <span class="st">"NDE"</span>, <span class="st">"RAND"</span>, <span class="st">"NONE"</span>)</a></code></pre></div>
</div>
<div id="number-of-successful-replicates" class="section level2 hasAnchor">
<h2><span class="header-section-number">6.4</span> Number of successful replicates<a href="conventional-genetic-programming-experiment.html#number-of-successful-replicates" class="anchor-section" aria-label="Anchor link to header"></a></h2>
<p>We considered a run to be successful if it produced a program capable of performing all 22 tasks during evaluation.</p>
<div class="sourceCode" id="cb19"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb19-1" title="1"><span class="kw">ggplot</span>(</a>
<a class="sourceLine" id="cb19-2" title="2"> <span class="kw">filter</span>(exp_summary_data, max_fit_is_solution<span class="op">==</span><span class="st">"1"</span>),</a>
<a class="sourceLine" id="cb19-3" title="3"> <span class="kw">aes</span>(<span class="dt">x=</span>SELECTION_METHOD, <span class="dt">fill=</span>SELECTION_METHOD)</a>
<a class="sourceLine" id="cb19-4" title="4"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb19-5" title="5"><span class="st"> </span><span class="kw">geom_bar</span>() <span class="op">+</span></a>
<a class="sourceLine" id="cb19-6" title="6"><span class="st"> </span><span class="kw">geom_text</span>(</a>
<a class="sourceLine" id="cb19-7" title="7"> <span class="dt">stat=</span><span class="st">"count"</span>,</a>
<a class="sourceLine" id="cb19-8" title="8"> <span class="dt">mapping=</span><span class="kw">aes</span>(<span class="dt">label=</span>..count..),</a>
<a class="sourceLine" id="cb19-9" title="9"> <span class="dt">position=</span><span class="kw">position_dodge</span>(<span class="fl">0.9</span>),</a>
<a class="sourceLine" id="cb19-10" title="10"> <span class="dt">vjust=</span><span class="dv">0</span></a>
<a class="sourceLine" id="cb19-11" title="11"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb19-12" title="12"><span class="st"> </span><span class="kw">scale_y_continuous</span>(</a>
<a class="sourceLine" id="cb19-13" title="13"> <span class="dt">limits=</span><span class="kw">c</span>(<span class="dv">0</span>, <span class="dv">50</span>),</a>
<a class="sourceLine" id="cb19-14" title="14"> <span class="dt">breaks=</span><span class="kw">seq</span>(<span class="dv">0</span>,<span class="dv">50</span>,<span class="dv">10</span>)</a>
<a class="sourceLine" id="cb19-15" title="15"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb19-16" title="16"><span class="st"> </span><span class="kw">scale_x_discrete</span>(</a>
<a class="sourceLine" id="cb19-17" title="17"> <span class="dt">name=</span><span class="st">"Selection Method"</span>,</a>
<a class="sourceLine" id="cb19-18" title="18"> <span class="dt">limits=</span>selection_method_breaks,</a>
<a class="sourceLine" id="cb19-19" title="19"> <span class="dt">breaks=</span>selection_method_breaks,</a>
<a class="sourceLine" id="cb19-20" title="20"> <span class="dt">labels=</span>selection_method_labels</a>
<a class="sourceLine" id="cb19-21" title="21"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb19-22" title="22"><span class="st"> </span><span class="kw">scale_fill_fun</span>(</a>
<a class="sourceLine" id="cb19-23" title="23"> <span class="dt">limits=</span>selection_method_breaks,</a>
<a class="sourceLine" id="cb19-24" title="24"> <span class="dt">breaks=</span>selection_method_breaks,</a>
<a class="sourceLine" id="cb19-25" title="25"> <span class="dt">labels=</span>selection_method_labels</a>
<a class="sourceLine" id="cb19-26" title="26"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb19-27" title="27"><span class="st"> </span><span class="kw">scale_color_fun</span>(</a>
<a class="sourceLine" id="cb19-28" title="28"> <span class="dt">limits=</span>selection_method_breaks,</a>
<a class="sourceLine" id="cb19-29" title="29"> <span class="dt">breaks=</span>selection_method_breaks,</a>
<a class="sourceLine" id="cb19-30" title="30"> <span class="dt">labels=</span>selection_method_labels</a>
<a class="sourceLine" id="cb19-31" title="31"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb19-32" title="32"><span class="st"> </span><span class="kw">ylab</span>(<span class="st">"Successful replicates"</span>) <span class="op">+</span></a>
<a class="sourceLine" id="cb19-33" title="33"><span class="st"> </span><span class="kw">theme</span>(<span class="dt">legend.position =</span> <span class="st">"none"</span>)</a></code></pre></div>
<p><img src="supplemental-material_files/figure-html/unnamed-chunk-7-1.png" width="672" /></p>
<div class="sourceCode" id="cb20"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb20-1" title="1"><span class="kw">ggsave</span>(</a>
<a class="sourceLine" id="cb20-2" title="2"> <span class="kw">paste0</span>(plot_directory, <span class="st">"2021-11-15-num-solutions.pdf"</span>)</a>
<a class="sourceLine" id="cb20-3" title="3">)</a></code></pre></div>
<pre><code>## Saving 7 x 5 in image</code></pre>
</div>
<div id="final-task-coverage" class="section level2 hasAnchor">
<h2><span class="header-section-number">6.5</span> Final task coverage<a href="conventional-genetic-programming-experiment.html#final-task-coverage" class="anchor-section" aria-label="Anchor link to header"></a></h2>
<p>Task coverage after 55,000 generations of evolution.</p>
<div class="sourceCode" id="cb22"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb22-1" title="1">max_task_cov_fig <-</a>
<a class="sourceLine" id="cb22-2" title="2"><span class="st"> </span><span class="kw">ggplot</span>(</a>
<a class="sourceLine" id="cb22-3" title="3"> exp_summary_data,</a>
<a class="sourceLine" id="cb22-4" title="4"> <span class="kw">aes</span>(</a>
<a class="sourceLine" id="cb22-5" title="5"> <span class="dt">x=</span>SELECTION_METHOD,</a>
<a class="sourceLine" id="cb22-6" title="6"> <span class="dt">y=</span>max_fit_aggregate_score,</a>
<a class="sourceLine" id="cb22-7" title="7"> <span class="dt">fill=</span>SELECTION_METHOD</a>
<a class="sourceLine" id="cb22-8" title="8"> )</a>
<a class="sourceLine" id="cb22-9" title="9"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb22-10" title="10"><span class="st"> </span><span class="kw">geom_flat_violin</span>(</a>
<a class="sourceLine" id="cb22-11" title="11"> <span class="dt">position =</span> <span class="kw">position_nudge</span>(<span class="dt">x =</span> <span class="fl">.2</span>, <span class="dt">y =</span> <span class="dv">0</span>),</a>
<a class="sourceLine" id="cb22-12" title="12"> <span class="dt">alpha =</span> <span class="fl">.8</span>,</a>
<a class="sourceLine" id="cb22-13" title="13"> <span class="dt">adjust=</span><span class="fl">1.5</span></a>
<a class="sourceLine" id="cb22-14" title="14"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb22-15" title="15"><span class="st"> </span><span class="kw">geom_point</span>(</a>
<a class="sourceLine" id="cb22-16" title="16"> <span class="dt">mapping=</span><span class="kw">aes</span>(<span class="dt">color=</span>SELECTION_METHOD),</a>
<a class="sourceLine" id="cb22-17" title="17"> <span class="dt">position =</span> <span class="kw">position_jitter</span>(<span class="dt">width =</span> <span class="fl">.15</span>),</a>
<a class="sourceLine" id="cb22-18" title="18"> <span class="dt">size =</span> <span class="fl">.5</span>,</a>
<a class="sourceLine" id="cb22-19" title="19"> <span class="dt">alpha =</span> <span class="fl">0.8</span></a>
<a class="sourceLine" id="cb22-20" title="20"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb22-21" title="21"><span class="st"> </span><span class="kw">geom_boxplot</span>(</a>
<a class="sourceLine" id="cb22-22" title="22"> <span class="dt">width =</span> <span class="fl">.1</span>,</a>
<a class="sourceLine" id="cb22-23" title="23"> <span class="dt">outlier.shape =</span> <span class="ot">NA</span>,</a>
<a class="sourceLine" id="cb22-24" title="24"> <span class="dt">alpha =</span> <span class="fl">0.5</span></a>
<a class="sourceLine" id="cb22-25" title="25"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb22-26" title="26"><span class="st"> </span><span class="kw">scale_y_continuous</span>(</a>
<a class="sourceLine" id="cb22-27" title="27"> <span class="dt">name=</span><span class="st">"Task Coverage"</span>,</a>
<a class="sourceLine" id="cb22-28" title="28"> <span class="dt">limits=</span><span class="kw">c</span>(<span class="op">-</span><span class="fl">0.5</span>,<span class="fl">22.5</span>),</a>
<a class="sourceLine" id="cb22-29" title="29"> <span class="dt">breaks=</span><span class="kw">seq</span>(<span class="dv">0</span>,<span class="dv">22</span>,<span class="dv">2</span>)</a>
<a class="sourceLine" id="cb22-30" title="30"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb22-31" title="31"><span class="st"> </span><span class="kw">scale_x_discrete</span>(</a>
<a class="sourceLine" id="cb22-32" title="32"> <span class="dt">name=</span><span class="st">"Selection Method"</span>,</a>
<a class="sourceLine" id="cb22-33" title="33"> <span class="dt">breaks=</span>selection_method_breaks,</a>
<a class="sourceLine" id="cb22-34" title="34"> <span class="dt">labels=</span>selection_method_labels</a>
<a class="sourceLine" id="cb22-35" title="35"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb22-36" title="36"><span class="st"> </span><span class="kw">scale_fill_fun</span>(</a>
<a class="sourceLine" id="cb22-37" title="37"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb22-38" title="38"><span class="st"> </span><span class="kw">scale_color_fun</span>(</a>
<a class="sourceLine" id="cb22-39" title="39"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb22-40" title="40"><span class="st"> </span><span class="kw">theme</span>(</a>
<a class="sourceLine" id="cb22-41" title="41"> <span class="dt">legend.position=</span><span class="st">"none"</span></a>
<a class="sourceLine" id="cb22-42" title="42"> <span class="co"># axis.text = element_text(size = 8),</span></a>
<a class="sourceLine" id="cb22-43" title="43"> <span class="co"># axis.title = element_text(size=10)</span></a>
<a class="sourceLine" id="cb22-44" title="44"> )</a>
<a class="sourceLine" id="cb22-45" title="45">max_task_cov_fig</a></code></pre></div>
<p><img src="supplemental-material_files/figure-html/unnamed-chunk-8-1.png" width="672" /></p>
<div class="sourceCode" id="cb23"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb23-1" title="1"><span class="kw">ggsave</span>(</a>
<a class="sourceLine" id="cb23-2" title="2"> <span class="dt">plot=</span>max_task_cov_fig,</a>
<a class="sourceLine" id="cb23-3" title="3"> <span class="dt">filename=</span><span class="kw">paste0</span>(plot_directory, <span class="st">"2021-11-15-ec-performance.pdf"</span>),</a>
<a class="sourceLine" id="cb23-4" title="4"> <span class="dt">height=</span><span class="dv">3</span>,</a>
<a class="sourceLine" id="cb23-5" title="5"> <span class="dt">width=</span><span class="dv">4</span></a>
<a class="sourceLine" id="cb23-6" title="6">)</a></code></pre></div>
<p>Statistical results:</p>
<div class="sourceCode" id="cb24"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb24-1" title="1"><span class="kw">kruskal.test</span>(</a>
<a class="sourceLine" id="cb24-2" title="2"> <span class="dt">formula=</span>max_fit_aggregate_score<span class="op">~</span>SELECTION_METHOD,</a>
<a class="sourceLine" id="cb24-3" title="3"> <span class="dt">data=</span>exp_summary_data</a>
<a class="sourceLine" id="cb24-4" title="4">)</a></code></pre></div>
<pre><code>##
## Kruskal-Wallis rank sum test
##
## data: max_fit_aggregate_score by SELECTION_METHOD
## Kruskal-Wallis chi-squared = 332.52, df = 6, p-value < 2.2e-16</code></pre>
<div class="sourceCode" id="cb26"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb26-1" title="1"><span class="co"># Kruskal-wallis is significant, so we do a post-hoc wilcoxon rank-sum.</span></a>
<a class="sourceLine" id="cb26-2" title="2"><span class="kw">pairwise.wilcox.test</span>(</a>
<a class="sourceLine" id="cb26-3" title="3"> <span class="dt">x=</span>exp_summary_data<span class="op">$</span>max_fit_aggregate_score,</a>
<a class="sourceLine" id="cb26-4" title="4"> <span class="dt">g=</span>exp_summary_data<span class="op">$</span>SELECTION_METHOD,</a>
<a class="sourceLine" id="cb26-5" title="5"> <span class="dt">p.adjust.method=</span><span class="st">"bonferroni"</span>,</a>
<a class="sourceLine" id="cb26-6" title="6">)</a></code></pre></div>
<pre><code>##
## Pairwise comparisons using Wilcoxon rank sum test with continuity correction
##
## data: exp_summary_data$max_fit_aggregate_score and exp_summary_data$SELECTION_METHOD
##
## elite elite-10 tourn lex nde random
## elite-10 0.0087 - - - - -
## tourn 1.8e-14 < 2e-16 - - - -
## lex < 2e-16 < 2e-16 < 2e-16 - - -
## nde < 2e-16 < 2e-16 1.7e-15 < 2e-16 - -
## random < 2e-16 < 2e-16 < 2e-16 < 2e-16 < 2e-16 -
## none < 2e-16 < 2e-16 < 2e-16 < 2e-16 < 2e-16 0.8360
##
## P value adjustment method: bonferroni</code></pre>
</div>
<div id="generation-2000-task-coverage" class="section level2 hasAnchor">
<h2><span class="header-section-number">6.6</span> Generation 2,000 task coverage<a href="conventional-genetic-programming-experiment.html#generation-2000-task-coverage" class="anchor-section" aria-label="Anchor link to header"></a></h2>
<p>Task coverage after 2,000 generations (i.e., the number of cycles runin the directed evolution experiments)</p>
<div class="sourceCode" id="cb28"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb28-1" title="1"><span class="kw">ggplot</span>(</a>
<a class="sourceLine" id="cb28-2" title="2"> exp_data_gen_<span class="dv">2000</span>,</a>
<a class="sourceLine" id="cb28-3" title="3"> <span class="kw">aes</span>(</a>
<a class="sourceLine" id="cb28-4" title="4"> <span class="dt">x=</span>SELECTION_METHOD,</a>
<a class="sourceLine" id="cb28-5" title="5"> <span class="dt">y=</span>max_org_task_coverage,</a>
<a class="sourceLine" id="cb28-6" title="6"> <span class="dt">fill=</span>SELECTION_METHOD</a>
<a class="sourceLine" id="cb28-7" title="7"> )</a>
<a class="sourceLine" id="cb28-8" title="8"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb28-9" title="9"><span class="st"> </span><span class="kw">geom_flat_violin</span>(</a>
<a class="sourceLine" id="cb28-10" title="10"> <span class="dt">position =</span> <span class="kw">position_nudge</span>(<span class="dt">x =</span> <span class="fl">.2</span>, <span class="dt">y =</span> <span class="dv">0</span>),</a>
<a class="sourceLine" id="cb28-11" title="11"> <span class="dt">alpha =</span> <span class="fl">.8</span>,</a>
<a class="sourceLine" id="cb28-12" title="12"> <span class="dt">adjust=</span><span class="fl">1.5</span></a>
<a class="sourceLine" id="cb28-13" title="13"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb28-14" title="14"><span class="st"> </span><span class="kw">geom_point</span>(</a>
<a class="sourceLine" id="cb28-15" title="15"> <span class="dt">mapping=</span><span class="kw">aes</span>(<span class="dt">color=</span>SELECTION_METHOD),</a>
<a class="sourceLine" id="cb28-16" title="16"> <span class="dt">position =</span> <span class="kw">position_jitter</span>(<span class="dt">width =</span> <span class="fl">.15</span>),</a>
<a class="sourceLine" id="cb28-17" title="17"> <span class="dt">size =</span> <span class="fl">.5</span>,</a>
<a class="sourceLine" id="cb28-18" title="18"> <span class="dt">alpha =</span> <span class="fl">0.8</span></a>
<a class="sourceLine" id="cb28-19" title="19"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb28-20" title="20"><span class="st"> </span><span class="kw">geom_boxplot</span>(</a>
<a class="sourceLine" id="cb28-21" title="21"> <span class="dt">width =</span> <span class="fl">.1</span>,</a>
<a class="sourceLine" id="cb28-22" title="22"> <span class="dt">outlier.shape =</span> <span class="ot">NA</span>,</a>
<a class="sourceLine" id="cb28-23" title="23"> <span class="dt">alpha =</span> <span class="fl">0.5</span></a>
<a class="sourceLine" id="cb28-24" title="24"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb28-25" title="25"><span class="st"> </span><span class="kw">scale_y_continuous</span>(</a>
<a class="sourceLine" id="cb28-26" title="26"> <span class="dt">name=</span><span class="st">"Task Coverage"</span>,</a>
<a class="sourceLine" id="cb28-27" title="27"> <span class="dt">limits=</span><span class="kw">c</span>(<span class="op">-</span><span class="fl">0.5</span>,<span class="fl">22.5</span>),</a>
<a class="sourceLine" id="cb28-28" title="28"> <span class="dt">breaks=</span><span class="kw">seq</span>(<span class="dv">0</span>,<span class="dv">22</span>,<span class="dv">2</span>)</a>
<a class="sourceLine" id="cb28-29" title="29"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb28-30" title="30"><span class="st"> </span><span class="kw">scale_x_discrete</span>(</a>
<a class="sourceLine" id="cb28-31" title="31"> <span class="dt">name=</span><span class="st">"Selection Method"</span>,</a>
<a class="sourceLine" id="cb28-32" title="32"> <span class="dt">breaks=</span>selection_method_breaks,</a>
<a class="sourceLine" id="cb28-33" title="33"> <span class="dt">labels=</span>selection_method_labels</a>
<a class="sourceLine" id="cb28-34" title="34"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb28-35" title="35"><span class="st"> </span><span class="kw">scale_fill_fun</span>() <span class="op">+</span></a>
<a class="sourceLine" id="cb28-36" title="36"><span class="st"> </span><span class="kw">scale_color_fun</span>() <span class="op">+</span></a>
<a class="sourceLine" id="cb28-37" title="37"><span class="st"> </span><span class="kw">theme</span>(</a>
<a class="sourceLine" id="cb28-38" title="38"> <span class="dt">legend.position=</span><span class="st">"none"</span>,</a>
<a class="sourceLine" id="cb28-39" title="39"> <span class="dt">axis.text =</span> <span class="kw">element_text</span>(<span class="dt">size =</span> <span class="dv">8</span>),</a>
<a class="sourceLine" id="cb28-40" title="40"> <span class="dt">axis.title =</span> <span class="kw">element_text</span>(<span class="dt">size=</span><span class="dv">10</span>)</a>
<a class="sourceLine" id="cb28-41" title="41"> )</a></code></pre></div>
<p><img src="supplemental-material_files/figure-html/unnamed-chunk-10-1.png" width="672" /></p>
<div class="sourceCode" id="cb29"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb29-1" title="1"><span class="kw">ggsave</span>(</a>
<a class="sourceLine" id="cb29-2" title="2"> <span class="dt">filename=</span><span class="kw">paste0</span>(plot_directory, <span class="st">"max_aggregate_score_gen_2000.pdf"</span>),</a>
<a class="sourceLine" id="cb29-3" title="3"> <span class="dt">height=</span><span class="dv">3</span>,</a>
<a class="sourceLine" id="cb29-4" title="4"> <span class="dt">width=</span><span class="dv">4</span></a>
<a class="sourceLine" id="cb29-5" title="5">)</a></code></pre></div>
<p>Statistical results:</p>
<div class="sourceCode" id="cb30"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb30-1" title="1"><span class="kw">kruskal.test</span>(</a>
<a class="sourceLine" id="cb30-2" title="2"> <span class="dt">formula=</span>max_org_task_coverage<span class="op">~</span>SELECTION_METHOD,</a>
<a class="sourceLine" id="cb30-3" title="3"> <span class="dt">data=</span>exp_data_gen_<span class="dv">2000</span></a>
<a class="sourceLine" id="cb30-4" title="4">)</a></code></pre></div>
<pre><code>##
## Kruskal-Wallis rank sum test
##
## data: max_org_task_coverage by SELECTION_METHOD
## Kruskal-Wallis chi-squared = 322.54, df = 6, p-value < 2.2e-16</code></pre>
<div class="sourceCode" id="cb32"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb32-1" title="1"><span class="co"># Kruskal-wallis is significant, so we do a post-hoc wilcoxon rank-sum.</span></a>
<a class="sourceLine" id="cb32-2" title="2"><span class="kw">pairwise.wilcox.test</span>(</a>
<a class="sourceLine" id="cb32-3" title="3"> <span class="dt">x=</span>exp_data_gen_<span class="dv">2000</span><span class="op">$</span>max_org_task_coverage,</a>
<a class="sourceLine" id="cb32-4" title="4"> <span class="dt">g=</span>exp_data_gen_<span class="dv">2000</span><span class="op">$</span>SELECTION_METHOD,</a>
<a class="sourceLine" id="cb32-5" title="5"> <span class="dt">p.adjust.method=</span><span class="st">"bonferroni"</span>,</a>
<a class="sourceLine" id="cb32-6" title="6">)</a></code></pre></div>
<pre><code>##
## Pairwise comparisons using Wilcoxon rank sum test with continuity correction
##
## data: exp_data_gen_2000$max_org_task_coverage and exp_data_gen_2000$SELECTION_METHOD
##
## elite elite-10 tourn lex nde random
## elite-10 1.4e-09 - - - - -
## tourn 0.0013 1.9e-14 - - - -
## lex < 2e-16 7.3e-15 < 2e-16 - - -
## nde 9.8e-14 2.3e-16 2.7e-11 < 2e-16 - -
## random < 2e-16 < 2e-16 < 2e-16 < 2e-16 < 2e-16 -
## none < 2e-16 < 2e-16 < 2e-16 < 2e-16 < 2e-16 1.0000
##
## P value adjustment method: bonferroni</code></pre>
</div>
<div id="population-level-task-coverage" class="section level2 hasAnchor">
<h2><span class="header-section-number">6.7</span> Population-level task coverage<a href="conventional-genetic-programming-experiment.html#population-level-task-coverage" class="anchor-section" aria-label="Anchor link to header"></a></h2>
<p>Task coverage across entire population after 55,000 generations of evolution.</p>
<div class="sourceCode" id="cb34"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb34-1" title="1"><span class="kw">ggplot</span>(</a>
<a class="sourceLine" id="cb34-2" title="2"> exp_summary_data,</a>
<a class="sourceLine" id="cb34-3" title="3"> <span class="kw">aes</span>(</a>
<a class="sourceLine" id="cb34-4" title="4"> <span class="dt">x=</span>SELECTION_METHOD,</a>
<a class="sourceLine" id="cb34-5" title="5"> <span class="dt">y=</span>population_num_tasks_covered,</a>
<a class="sourceLine" id="cb34-6" title="6"> <span class="dt">fill=</span>SELECTION_METHOD</a>
<a class="sourceLine" id="cb34-7" title="7"> )</a>
<a class="sourceLine" id="cb34-8" title="8"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb34-9" title="9"><span class="st"> </span><span class="kw">geom_flat_violin</span>(</a>
<a class="sourceLine" id="cb34-10" title="10"> <span class="dt">position =</span> <span class="kw">position_nudge</span>(<span class="dt">x =</span> <span class="fl">.2</span>, <span class="dt">y =</span> <span class="dv">0</span>),</a>
<a class="sourceLine" id="cb34-11" title="11"> <span class="dt">alpha =</span> <span class="fl">.8</span></a>
<a class="sourceLine" id="cb34-12" title="12"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb34-13" title="13"><span class="st"> </span><span class="kw">geom_point</span>(</a>
<a class="sourceLine" id="cb34-14" title="14"> <span class="dt">mapping=</span><span class="kw">aes</span>(<span class="dt">color=</span>SELECTION_METHOD),</a>
<a class="sourceLine" id="cb34-15" title="15"> <span class="dt">position =</span> <span class="kw">position_jitter</span>(<span class="dt">width =</span> <span class="fl">.15</span>),</a>
<a class="sourceLine" id="cb34-16" title="16"> <span class="dt">size =</span> <span class="fl">.5</span>,</a>
<a class="sourceLine" id="cb34-17" title="17"> <span class="dt">alpha =</span> <span class="fl">0.8</span></a>
<a class="sourceLine" id="cb34-18" title="18"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb34-19" title="19"><span class="st"> </span><span class="kw">geom_boxplot</span>(</a>
<a class="sourceLine" id="cb34-20" title="20"> <span class="dt">width =</span> <span class="fl">.1</span>,</a>
<a class="sourceLine" id="cb34-21" title="21"> <span class="dt">outlier.shape =</span> <span class="ot">NA</span>,</a>
<a class="sourceLine" id="cb34-22" title="22"> <span class="dt">alpha =</span> <span class="fl">0.5</span></a>
<a class="sourceLine" id="cb34-23" title="23"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb34-24" title="24"><span class="st"> </span><span class="kw">scale_fill_fun</span>() <span class="op">+</span></a>
<a class="sourceLine" id="cb34-25" title="25"><span class="st"> </span><span class="kw">scale_color_fun</span>() <span class="op">+</span></a>
<a class="sourceLine" id="cb34-26" title="26"><span class="st"> </span><span class="kw">theme</span>(</a>
<a class="sourceLine" id="cb34-27" title="27"> <span class="dt">legend.position=</span><span class="st">"none"</span></a>
<a class="sourceLine" id="cb34-28" title="28"> )</a></code></pre></div>
<p><img src="supplemental-material_files/figure-html/unnamed-chunk-12-1.png" width="672" /></p>
<div class="sourceCode" id="cb35"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb35-1" title="1"><span class="kw">ggsave</span>(</a>
<a class="sourceLine" id="cb35-2" title="2"> <span class="kw">paste0</span>(plot_directory, <span class="st">"population_num_tasks_covered.pdf"</span>)</a>
<a class="sourceLine" id="cb35-3" title="3">)</a></code></pre></div>
<pre><code>## Saving 7 x 5 in image</code></pre>
</div>
<div id="generations-elapsed-before-a-solution-evolves" class="section level2 hasAnchor">
<h2><span class="header-section-number">6.8</span> Generations elapsed before a solution evolves<a href="conventional-genetic-programming-experiment.html#generations-elapsed-before-a-solution-evolves" class="anchor-section" aria-label="Anchor link to header"></a></h2>
<p>Runs where no solution evolved are in gray and plotted as “unsolved”.</p>
<div class="sourceCode" id="cb37"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb37-1" title="1">unfinished_data <-<span class="st"> </span><span class="kw">filter</span>(exp_summary_data, max_fit_is_solution<span class="op">==</span><span class="st">"0"</span>)</a>
<a class="sourceLine" id="cb37-2" title="2">unfinished_data<span class="op">$</span>graph_update <-<span class="st"> </span><span class="dv">60000</span></a>
<a class="sourceLine" id="cb37-3" title="3"></a>
<a class="sourceLine" id="cb37-4" title="4"><span class="kw">ggplot</span>(</a>
<a class="sourceLine" id="cb37-5" title="5"> <span class="kw">filter</span>(exp_summary_data, max_fit_is_solution<span class="op">==</span><span class="st">"1"</span>),</a>
<a class="sourceLine" id="cb37-6" title="6"> <span class="kw">aes</span>(</a>
<a class="sourceLine" id="cb37-7" title="7"> <span class="dt">x=</span>SELECTION_METHOD,</a>
<a class="sourceLine" id="cb37-8" title="8"> <span class="dt">y=</span>update</a>
<a class="sourceLine" id="cb37-9" title="9"> )</a>
<a class="sourceLine" id="cb37-10" title="10"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb37-11" title="11"><span class="st"> </span><span class="kw">geom_flat_violin</span>(</a>
<a class="sourceLine" id="cb37-12" title="12"> <span class="dt">position =</span> <span class="kw">position_nudge</span>(<span class="dt">x =</span> <span class="fl">.2</span>, <span class="dt">y =</span> <span class="dv">0</span>),</a>
<a class="sourceLine" id="cb37-13" title="13"> <span class="dt">alpha =</span> <span class="fl">.8</span></a>
<a class="sourceLine" id="cb37-14" title="14"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb37-15" title="15"><span class="st"> </span><span class="kw">geom_point</span>(</a>
<a class="sourceLine" id="cb37-16" title="16"> <span class="dt">position =</span> <span class="kw">position_jitter</span>(<span class="dt">width =</span> <span class="fl">.15</span>),</a>
<a class="sourceLine" id="cb37-17" title="17"> <span class="dt">size =</span> <span class="fl">.5</span>,</a>
<a class="sourceLine" id="cb37-18" title="18"> <span class="dt">alpha =</span> <span class="fl">0.8</span></a>
<a class="sourceLine" id="cb37-19" title="19"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb37-20" title="20"><span class="st"> </span><span class="kw">geom_point</span>(</a>
<a class="sourceLine" id="cb37-21" title="21"> <span class="dt">data =</span> unfinished_data,</a>
<a class="sourceLine" id="cb37-22" title="22"> <span class="dt">mapping=</span><span class="kw">aes</span>(</a>
<a class="sourceLine" id="cb37-23" title="23"> <span class="dt">x=</span>SELECTION_METHOD,</a>
<a class="sourceLine" id="cb37-24" title="24"> <span class="dt">y=</span>graph_update</a>
<a class="sourceLine" id="cb37-25" title="25"> ),</a>
<a class="sourceLine" id="cb37-26" title="26"> <span class="dt">color=</span><span class="st">"gray"</span>,</a>
<a class="sourceLine" id="cb37-27" title="27"> <span class="dt">position =</span> <span class="kw">position_jitter</span>(<span class="dt">width =</span> <span class="fl">.15</span>, <span class="dt">height=</span><span class="dv">1000</span>),</a>
<a class="sourceLine" id="cb37-28" title="28"> <span class="dt">size =</span> <span class="fl">.5</span>,</a>
<a class="sourceLine" id="cb37-29" title="29"> <span class="dt">alpha =</span> <span class="fl">0.8</span></a>
<a class="sourceLine" id="cb37-30" title="30"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb37-31" title="31"><span class="st"> </span><span class="kw">geom_boxplot</span>(</a>
<a class="sourceLine" id="cb37-32" title="32"> <span class="dt">width =</span> <span class="fl">.1</span>,</a>
<a class="sourceLine" id="cb37-33" title="33"> <span class="dt">outlier.shape =</span> <span class="ot">NA</span>,</a>
<a class="sourceLine" id="cb37-34" title="34"> <span class="dt">alpha =</span> <span class="fl">0.5</span></a>
<a class="sourceLine" id="cb37-35" title="35"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb37-36" title="36"><span class="st"> </span><span class="kw">scale_y_continuous</span>(</a>
<a class="sourceLine" id="cb37-37" title="37"> <span class="dt">name=</span><span class="st">"Generation first solution evolved"</span>,</a>
<a class="sourceLine" id="cb37-38" title="38"> <span class="dt">limits=</span><span class="kw">c</span>(<span class="dv">0</span>, <span class="dv">65000</span>),</a>
<a class="sourceLine" id="cb37-39" title="39"> <span class="dt">breaks=</span><span class="kw">c</span>(<span class="dv">0</span>, <span class="dv">10000</span>, <span class="dv">20000</span>, <span class="dv">30000</span>, <span class="dv">40000</span>, <span class="dv">50000</span>, <span class="dv">60000</span>),</a>
<a class="sourceLine" id="cb37-40" title="40"> <span class="dt">labels=</span><span class="kw">c</span>(<span class="st">"0"</span>, <span class="st">"10000"</span>, <span class="st">"20000"</span>, <span class="st">"30000"</span>, <span class="st">"40000"</span>, <span class="st">"50000"</span>, <span class="st">"Unsolved"</span>)</a>
<a class="sourceLine" id="cb37-41" title="41"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb37-42" title="42"><span class="st"> </span><span class="kw">theme</span>(</a>
<a class="sourceLine" id="cb37-43" title="43"> <span class="dt">legend.position=</span><span class="st">"none"</span></a>
<a class="sourceLine" id="cb37-44" title="44"> )</a></code></pre></div>
<pre><code>## Warning: Groups with fewer than two data points have been dropped.</code></pre>
<p><img src="supplemental-material_files/figure-html/unnamed-chunk-13-1.png" width="672" /></p>
<div class="sourceCode" id="cb39"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb39-1" title="1"><span class="kw">ggsave</span>(</a>
<a class="sourceLine" id="cb39-2" title="2"> <span class="kw">paste0</span>(plot_directory, <span class="st">"updates_until_solution.pdf"</span>)</a>
<a class="sourceLine" id="cb39-3" title="3">)</a></code></pre></div>
<pre><code>## Saving 7 x 5 in image</code></pre>
<pre><code>## Warning: Groups with fewer than two data points have been dropped.</code></pre>
</div>
<div id="best-task-coverage-over-time" class="section level2 hasAnchor">
<h2><span class="header-section-number">6.9</span> Best task coverage over time<a href="conventional-genetic-programming-experiment.html#best-task-coverage-over-time" class="anchor-section" aria-label="Anchor link to header"></a></h2>
<div class="sourceCode" id="cb42"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb42-1" title="1">max_task_cov_ts <-</a>
<a class="sourceLine" id="cb42-2" title="2"><span class="st"> </span><span class="kw">ggplot</span>(</a>
<a class="sourceLine" id="cb42-3" title="3"> time_series_data,</a>
<a class="sourceLine" id="cb42-4" title="4"> <span class="kw">aes</span>(</a>
<a class="sourceLine" id="cb42-5" title="5"> <span class="dt">x=</span>update,</a>
<a class="sourceLine" id="cb42-6" title="6"> <span class="dt">y=</span>max_org_task_coverage,</a>
<a class="sourceLine" id="cb42-7" title="7"> <span class="dt">fill=</span>SELECTION_METHOD,</a>
<a class="sourceLine" id="cb42-8" title="8"> <span class="dt">color=</span>SELECTION_METHOD</a>
<a class="sourceLine" id="cb42-9" title="9"> )</a>
<a class="sourceLine" id="cb42-10" title="10"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb42-11" title="11"><span class="st"> </span><span class="kw">stat_summary</span>(<span class="dt">geom=</span><span class="st">"line"</span>, <span class="dt">fun=</span>mean) <span class="op">+</span></a>
<a class="sourceLine" id="cb42-12" title="12"><span class="st"> </span><span class="kw">stat_summary</span>(</a>
<a class="sourceLine" id="cb42-13" title="13"> <span class="dt">geom=</span><span class="st">"ribbon"</span>,</a>
<a class="sourceLine" id="cb42-14" title="14"> <span class="dt">fun.data=</span><span class="st">"mean_cl_boot"</span>,</a>
<a class="sourceLine" id="cb42-15" title="15"> <span class="dt">fun.args=</span><span class="kw">list</span>(<span class="dt">conf.int=</span><span class="fl">0.95</span>),</a>
<a class="sourceLine" id="cb42-16" title="16"> <span class="dt">alpha=</span><span class="fl">0.2</span>,</a>
<a class="sourceLine" id="cb42-17" title="17"> <span class="dt">linetype=</span><span class="dv">0</span></a>
<a class="sourceLine" id="cb42-18" title="18"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb42-19" title="19"><span class="st"> </span><span class="kw">scale_y_continuous</span>(</a>
<a class="sourceLine" id="cb42-20" title="20"> <span class="dt">name=</span><span class="st">"Task Coverage"</span>,</a>
<a class="sourceLine" id="cb42-21" title="21"> <span class="dt">limits=</span><span class="kw">c</span>(<span class="op">-</span><span class="fl">0.5</span>,<span class="fl">22.5</span>),</a>
<a class="sourceLine" id="cb42-22" title="22"> <span class="dt">breaks=</span><span class="kw">seq</span>(<span class="dv">0</span>,<span class="dv">22</span>,<span class="dv">2</span>)</a>
<a class="sourceLine" id="cb42-23" title="23"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb42-24" title="24"><span class="st"> </span><span class="kw">scale_x_continuous</span>(</a>
<a class="sourceLine" id="cb42-25" title="25"> <span class="dt">name=</span><span class="st">"Generation"</span>,</a>
<a class="sourceLine" id="cb42-26" title="26"> <span class="dt">limits=</span><span class="kw">c</span>(<span class="dv">0</span>, <span class="dv">55000</span>),</a>
<a class="sourceLine" id="cb42-27" title="27"> <span class="dt">breaks=</span><span class="kw">c</span>(<span class="dv">0</span>, <span class="dv">10000</span>, <span class="dv">20000</span>, <span class="dv">30000</span>, <span class="dv">40000</span>, <span class="dv">50000</span>)</a>
<a class="sourceLine" id="cb42-28" title="28"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb42-29" title="29"><span class="st"> </span><span class="kw">scale_fill_fun</span>(</a>
<a class="sourceLine" id="cb42-30" title="30"> <span class="dt">name=</span><span class="st">"Selection method"</span>,</a>
<a class="sourceLine" id="cb42-31" title="31"> <span class="dt">breaks=</span>selection_method_breaks,</a>
<a class="sourceLine" id="cb42-32" title="32"> <span class="dt">labels=</span>selection_method_labels</a>
<a class="sourceLine" id="cb42-33" title="33"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb42-34" title="34"><span class="st"> </span><span class="kw">scale_color_fun</span>(</a>
<a class="sourceLine" id="cb42-35" title="35"> <span class="dt">name=</span><span class="st">"Selection method"</span>,</a>
<a class="sourceLine" id="cb42-36" title="36"> <span class="dt">breaks=</span>selection_method_breaks,</a>
<a class="sourceLine" id="cb42-37" title="37"> <span class="dt">labels=</span>selection_method_labels</a>
<a class="sourceLine" id="cb42-38" title="38"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb42-39" title="39"><span class="st"> </span><span class="kw">theme</span>(</a>
<a class="sourceLine" id="cb42-40" title="40"> <span class="dt">legend.position=</span><span class="st">"none"</span></a>
<a class="sourceLine" id="cb42-41" title="41"> )</a>
<a class="sourceLine" id="cb42-42" title="42">max_task_cov_ts</a></code></pre></div>
<pre><code>## Warning: Computation failed in `stat_summary()`:</code></pre>
<p><img src="supplemental-material_files/figure-html/unnamed-chunk-14-1.png" width="672" /></p>
<div class="sourceCode" id="cb44"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb44-1" title="1"><span class="kw">ggsave</span>(</a>
<a class="sourceLine" id="cb44-2" title="2"> <span class="kw">paste0</span>(plot_directory, <span class="st">"2021-11-15-ec-performance-ts.pdf"</span>)</a>
<a class="sourceLine" id="cb44-3" title="3">)</a></code></pre></div>
<pre><code>## Saving 7 x 5 in image</code></pre>
<pre><code>## Warning: Computation failed in `stat_summary()`:</code></pre>
</div>
<div id="manuscript-figure" class="section level2 hasAnchor">
<h2><span class="header-section-number">6.10</span> Manuscript Figure<a href="conventional-genetic-programming-experiment.html#manuscript-figure" class="anchor-section" aria-label="Anchor link to header"></a></h2>
<div class="sourceCode" id="cb47"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb47-1" title="1">legend <-<span class="st"> </span>cowplot<span class="op">::</span><span class="kw">get_legend</span>(</a>
<a class="sourceLine" id="cb47-2" title="2"> max_task_cov_ts <span class="op">+</span></a>
<a class="sourceLine" id="cb47-3" title="3"><span class="st"> </span><span class="kw">guides</span>(</a>
<a class="sourceLine" id="cb47-4" title="4"> <span class="dt">color=</span><span class="kw">guide_legend</span>(<span class="dt">nrow=</span><span class="dv">1</span>),</a>
<a class="sourceLine" id="cb47-5" title="5"> <span class="dt">fill=</span><span class="kw">guide_legend</span>(<span class="dt">nrow=</span><span class="dv">1</span>)</a>
<a class="sourceLine" id="cb47-6" title="6"> ) <span class="op">+</span></a>
<a class="sourceLine" id="cb47-7" title="7"><span class="st"> </span><span class="kw">theme</span>(</a>
<a class="sourceLine" id="cb47-8" title="8"> <span class="dt">legend.position =</span> <span class="st">"bottom"</span>,</a>
<a class="sourceLine" id="cb47-9" title="9"> <span class="dt">legend.box=</span><span class="st">"horizontal"</span>,</a>
<a class="sourceLine" id="cb47-10" title="10"> <span class="dt">legend.justification=</span><span class="st">"center"</span></a>
<a class="sourceLine" id="cb47-11" title="11"> )</a>
<a class="sourceLine" id="cb47-12" title="12"> )</a></code></pre></div>
<pre><code>## Warning: Computation failed in `stat_summary()`:</code></pre>
<div class="sourceCode" id="cb49"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb49-1" title="1">grid <-<span class="st"> </span><span class="kw">plot_grid</span>(</a>
<a class="sourceLine" id="cb49-2" title="2"> max_task_cov_ts <span class="op">+</span></a>
<a class="sourceLine" id="cb49-3" title="3"><span class="st"> </span><span class="kw">ggtitle</span>(<span class="st">"Task coverage over time"</span>) <span class="op">+</span></a>
<a class="sourceLine" id="cb49-4" title="4"><span class="st"> </span><span class="kw">labs</span>(<span class="dt">subtitle=</span><span class="st">""</span>) <span class="op">+</span></a>
<a class="sourceLine" id="cb49-5" title="5"><span class="st"> </span><span class="kw">theme</span>(<span class="dt">legend.position=</span><span class="st">"none"</span>),</a>
<a class="sourceLine" id="cb49-6" title="6"> max_task_cov_fig <span class="op">+</span></a>
<a class="sourceLine" id="cb49-7" title="7"><span class="st"> </span><span class="kw">ggtitle</span>(<span class="st">"Final task coverage"</span>) <span class="op">+</span></a>
<a class="sourceLine" id="cb49-8" title="8"><span class="st"> </span><span class="kw">theme</span>(),</a>
<a class="sourceLine" id="cb49-9" title="9"> <span class="dt">nrow=</span><span class="dv">1</span>,</a>
<a class="sourceLine" id="cb49-10" title="10"> <span class="dt">ncol=</span><span class="dv">2</span>,</a>
<a class="sourceLine" id="cb49-11" title="11"> <span class="dt">align=</span><span class="st">"h"</span>,</a>
<a class="sourceLine" id="cb49-12" title="12"> <span class="co"># rel_widths=c(3,2),</span></a>
<a class="sourceLine" id="cb49-13" title="13"> <span class="dt">labels=</span><span class="st">"auto"</span></a>
<a class="sourceLine" id="cb49-14" title="14">)</a></code></pre></div>
<pre><code>## Warning: Computation failed in `stat_summary()`:</code></pre>
<div class="sourceCode" id="cb51"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb51-1" title="1"><span class="co"># grid</span></a>
<a class="sourceLine" id="cb51-2" title="2">grid <-<span class="st"> </span><span class="kw">plot_grid</span>(</a>
<a class="sourceLine" id="cb51-3" title="3"> grid,</a>
<a class="sourceLine" id="cb51-4" title="4"> legend,</a>
<a class="sourceLine" id="cb51-5" title="5"> <span class="dt">nrow=</span><span class="dv">2</span>,</a>
<a class="sourceLine" id="cb51-6" title="6"> <span class="dt">ncol=</span><span class="dv">1</span>,</a>
<a class="sourceLine" id="cb51-7" title="7"> <span class="dt">rel_heights=</span><span class="kw">c</span>(<span class="dv">1</span>, <span class="fl">0.1</span>)</a>
<a class="sourceLine" id="cb51-8" title="8">)</a>
<a class="sourceLine" id="cb51-9" title="9">grid</a></code></pre></div>
<p><img src="supplemental-material_files/figure-html/unnamed-chunk-15-1.png" width="672" /></p>
<div class="sourceCode" id="cb52"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb52-1" title="1"><span class="kw">save_plot</span>(</a>
<a class="sourceLine" id="cb52-2" title="2"> <span class="kw">paste</span>(</a>
<a class="sourceLine" id="cb52-3" title="3"> plot_directory,</a>
<a class="sourceLine" id="cb52-4" title="4"> <span class="st">"2021-11-15-performance-fig.pdf"</span>,</a>
<a class="sourceLine" id="cb52-5" title="5"> <span class="dt">sep=</span><span class="st">""</span></a>
<a class="sourceLine" id="cb52-6" title="6"> ),</a>
<a class="sourceLine" id="cb52-7" title="7"> grid,</a>
<a class="sourceLine" id="cb52-8" title="8"> <span class="dt">base_width=</span><span class="dv">12</span>,</a>
<a class="sourceLine" id="cb52-9" title="9"> <span class="dt">base_height=</span><span class="dv">6</span></a>
<a class="sourceLine" id="cb52-10" title="10">)</a></code></pre></div>
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