// the find
MorvanZhou/Evolutionary-Algorithm
Evolutionary Algorithm using Python, 莫烦Python 中文AI教学
A collection of small, standalone Python scripts implementing classic evolutionary computation methods — GA, microbial GA, (1+1)-ES, NES, and NEAT (supervised and gym-based RL) — plus a distributed ES-with-neural-nets example modeled on OpenAI's approach. It's a companion codebase to a Chinese-language video tutorial series, aimed at people who want to see how these algorithms work mechanically rather than use a production library.
Each script is short and self-contained, so you can read the whole GA or NES implementation in one sitting instead of digging through a framework's abstractions. The paired gif demos (TSP tours, pathfinding, phrase matching) make the effect of each algorithm visible rather than just printing a fitness number. Decent breadth for a single repo — it goes from basic GA through NES to NEAT and distributed ES, covering most of the entry points into the field.
No requirements.txt or dependency pinning anywhere in the tree, so getting these scripts running on a current Python install is trial and error. Last commit is from November 2023 and NEAT_gym is written against the old `gym` API, which has since been superseded by `gymnasium` — expect import errors out of the box. There's no packaging, no tests, no CI; this is a pile of teaching scripts, not something you `pip install` and build on. The actual explanations live behind an external Chinese video course, so the code alone won't teach you the theory if you don't already know it.