|Linux	|Windows

:—:|:—:|:—: Master | Build Status|Build status

Development | Build Status|Build status


Visualization Tool by @Mafii
Experimental image recognition is currently being added at https://github.com/IDPA16/Hippocrates

Implementation of Kenneth Stanley and Risto Miikkulainen’s NEAT (NeuroEvolution of Augmenting Topologies, http://nn.cs.utexas.edu/downloads/papers/stanley.ec02.pdf).

It focuses (in contrast to other implementations) on

  • Speed - through modern and efficient C++17
  • Clean Code - through constant ongoing refactoring and a deep care for aesthetics
  • Usability - through being able to be used without much knowledge of Neural Networks
  • Platform Independency - written on three different operating systems (Windows, Ubuntu, MacOS X) and the most used compilers (MSVC and GCC6), it is safe to say that it will work on multiple platforms, flawlessly.


  • Serge A. Zaitsev (jsmn)