adipandas / pyneat

NEAT: NeuroEvolution of Augmenting Topologies

pyneat

This is an implementation of NEAT: NeuroEvolution of Augmenting Topologies in Python.

Environments	Plot (reward vs. generations)	Evolved Neural Network Architecture

Installation

pip install numpy scipy matplotlib
conda install pygraphviz
pip install networkx

Installation of OpenAI Gym: [link]

How to use?

This is a minimal implementation of NEAT. I haven't used any sort of parallel computing tricks like multiprocessing over here. The implementation should be fairly easy to understand.

python run_neat.py --help

python run_neat.py --task=lunar   # Run NEAT to learn lunar-lander policy

For any customization:

• Different tasks: Edit run_neat.py
• Hyperparameters: Edit pyneat/config.py

References:

• Stanley, Kenneth O., and Risto Miikkulainen. "Efficient evolution of neural network topologies." Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No. 02TH8600). Vol. 2. IEEE, 2002.
• neat-python: https://github.com/CodeReclaimers/neat-python

Refer the following implementation for additional (advanced) functionalities.

• https://github.com/google/brain-tokyo-workshop/tree/master/WANNRelease/prettyNEAT
• MultiNEAT
• pureples

Please let me know if you come across any bugs in this implementation. Feel free to send any pull requests.