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.

Note

Some of the example code has other dependencies; please see each example’s README.md file for additional details and installation/setup instructions for the main code for each. In addition to dependencies varying with different examples, visualization of the results (via visualize.py modules) frequently requires graphviz and/or matplotlib. TODO: Improve README.md file information for the examples.

Support for HyperNEAT and other extensions to NEAT is planned once the fundamental NEAT implementation is more complete and stable.

For further information regarding general concepts and theory, please see Selected Publications on Stanley’s website, or his recent AMA on Reddit.

If you encounter any confusing or incorrect information in this documentation, please open an issue in the GitHub project.

Contents:

Indices and tables