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<p dir="ltr"><span style="background-color:transparent; color:#000000; font-family:arial,sans-serif; font-size:11pt">Types of runs I need (May need some other people to help me run these):</span></p>
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<p dir="ltr"><span style="background-color:transparent; color:#000000; font-family:arial,sans-serif; font-size:11pt">Optimization runs</span></p>
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<p dir="ltr"><span style="background-color:transparent; color:#000000; font-family:arial,sans-serif; font-size:11pt">Non-error</span></p>
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<p dir="ltr"><span style="background-color:transparent; color:#000000; font-family:arial,sans-serif; font-size:11pt">Search over combinations of selection methods and genetic operators</span></p>
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<p dir="ltr"><span style="background-color:transparent; color:#000000; font-family:arial,sans-serif; font-size:11pt">Fix Sigma at 10%.</span></p>
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<p dir="ltr"><span style="background-color:transparent; color:#000000; font-family:arial,sans-serif; font-size:11pt">Do this for 10 runs for each </span></p>
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<p dir="ltr"><span style="background-color:transparent; color:#000000; font-family:arial,sans-serif; font-size:11pt">Re-run the best run for 100 tests to see if the results agree with 10 test results</span></p>
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<p dir="ltr"><span style="background-color:transparent; color:#000000; font-family:arial,sans-serif; font-size:11pt">This will be the main talking point</span></p>
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<p dir="ltr"><span style="background-color:transparent; color:#000000; font-family:arial,sans-serif; font-size:11pt">Save the plot for the best combination (proxy and metric)</span></p>
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<p dir="ltr"><span style="background-color:transparent; color:#000000; font-family:arial,sans-serif; font-size:11pt">Error</span></p>
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<p dir="ltr"><span style="background-color:transparent; color:#000000; font-family:arial,sans-serif; font-size:11pt">Re-run the best run for 100 tests with 3 different error amounts (0.1, 0.2, 0.3)</span></p>
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<p dir="ltr"><span style="background-color:transparent; color:#000000; font-family:arial,sans-serif; font-size:11pt">We will compare these results to the non-error run to talk about how errors may affect consistency/speed. </span></p>
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<p dir="ltr"><span style="background-color:transparent; color:#000000; font-family:arial,sans-serif; font-size:11pt">Save an example plot of an error test for each error (both metric and proxy score)</span></p>
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<p dir="ltr"><span style="background-color:transparent; color:#000000; font-family:arial,sans-serif; font-size:11pt">Population</span></p>
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<p dir="ltr"><span style="background-color:transparent; color:#000000; font-family:arial,sans-serif; font-size:11pt">Re-run the best run for 100 tests with 3 different population sizes (100, 500, 1000)</span></p>
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<li dir="ltr">
<p dir="ltr"><span style="background-color:transparent; color:#000000; font-family:arial,sans-serif; font-size:11pt">We will compare these results to the non-error run to talk about how population size affects consistency/speed. </span></p>
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<p dir="ltr"><span style="background-color:transparent; color:#000000; font-family:arial,sans-serif; font-size:11pt">Save an example plot of a population test for each size (just proxy score)</span></p>
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<p dir="ltr"><span style="background-color:transparent; color:#000000; font-family:arial,sans-serif; font-size:11pt">Demonstration runs (single runs, fitness score, no error population 100)</span></p>
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<p dir="ltr"><span style="background-color:transparent; color:#000000; font-family:arial,sans-serif; font-size:11pt">Crossover only</span></p>
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<p dir="ltr"><span style="background-color:transparent; color:#000000; font-family:arial,sans-serif; font-size:11pt">Mutation only</span></p>
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<p dir="ltr"><span style="background-color:transparent; color:#000000; font-family:arial,sans-serif; font-size:11pt">Reproduction only</span></p>
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<p dir="ltr"><span style="background-color:transparent; color:#000000; font-family:arial,sans-serif; font-size:11pt">Injection only</span></p>
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