NEAT (NeuroEvolution of Augmenting Topologies) 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 sample code has other dependencies; please see each sample's README file for additional details and installation/setup instructions.
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:
.. toctree:: :maxdepth: 2 neat_overview installation config_file xor_example customization activation ctrnn genome-interface