Today, I ported SpeedyGA from Matlab to Python. SpeedyGApy is a configurable, single-file, barebones, vectorized, numpy + matplotlib based genetic algorithm that rips.
The following video shows the kind of animation that gets displayed when speedyGA is run on a staircase function. Animations like this one serve as proof-of-concept for the Hyperclimbing Hypothesis, a new explanation for optimization in genetic algorithms with uniform crossover. Once you’ve downloaded speedyGApy, you can run this, and other experiments for yourself with the following command:
$ python speedyGA.py --fitnessFunction staircase
evorithmics 