Intro

This week, I’ll make it short, and instead of boring with code and explanations, I thought I’d just show an example output…

Results

This is a genetic algorithm in action: A population “evolves” (reproduces, “selection of the fittest”, iterate) towards an objective. Complexity of many local minima don’t seem to be an issue for this algorithm. The below shows population over 5 frames extracted from 50 generations at regular intervals.

Notes

This example is quite simple, really. I have yet to implement “mutations”, and I chose one of many possible mixes of parents selection, as well as the most simple crossing of parents to create children.

But it still works 🙂

Next time

I’ll throw in mutations, and then share the code for what you can observe above. And maybe some considerations.