Welcome to NEAT-Python’s documentation!¶
NEAT is a method developed by Kenneth O. Stanley for evolving arbitrary neural networks. NEAT-Python is a pure Python implementation of NEAT, with no dependencies other than the Python standard library.
Currently this library supports Python versions 3.6 through 3.11, as well as PyPy 3.
Many thanks to the original authors of this implementation, Cesar Gomes Miguel, Carolina Feher da Silva, and Marcio Lobo Netto!
Some of the example code has other dependencies. For your convenience there is a conda environment YAML file in the examples directory you can use to set up an environment that will support all of the current examples. TODO: Improve README.md file information for the examples.
If you encounter any confusing or incorrect information in this documentation, please open an issue in the GitHub project.
- NEAT Overview
- Configuration file description
- Overview of the basic XOR example (evolve-feedforward.py)
- Customizing Behavior
- Overview of builtin activation functions
- Continuous-time recurrent neural network implementation
- Module summaries
- Genome Interface
- Reproduction Interface