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@MashAliK
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Handful of changes to the Function Minimization example that improve robustness during evolution and result in a (in my opinion) better search function at the end. Summary of changes:

  • During a run the program got stuck at iteration ~900 so I made a change to use multiprocessing instead of concurrent.features because the latter uses threads which, turns out, can't actually be killed from within the control loop
  • Add a metric which accounts for the standard deviation of the x and y values. Without these, the values tend to fluctuate too much when calling the generated search functions
  • Removed unnecessary calls to safe_float and float
  • Removed value and distance from evaluate_stage1 since they aren't metrics (might not have values between 0 and 1)
  • Updated the README to include an example generated with the new evaluator and included its results
  • Exclude evaluate_function from Evolve Block scope because this function shouldn't be modified

@codelion
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@MashAliK thanks for the contribution can you fix the linting errors by running black openevolve tests examples as mentioned in https://github.com/codelion/openevolve/blob/main/CONTRIBUTING.md#code-style

@codelion codelion merged commit 153f5a7 into algorithmicsuperintelligence:main May 27, 2025
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2 participants