MultiNEAT is a portable software library for performing neuroevolution, a form of machine learning that trains neural networks with a genetic algorithm. It is based on NEAT, an advanced method for evolving neural networks through complexification. The neural networks in NEAT begin evolution with very simple genomes which grow over successive generations. The individuals in the evolving population are grouped by similarity into species, and each of them can compete only with the individuals in the same species.
The combined effect of speciation, starting from the simplest initial structure and the correct matching of the genomes through marking genes with historical markings yields an algorithm which is proven to be very effective in many domains and benchmarks against other methods.
NEAT was developed around 2002 by Kenneth Stanley in the University of Texas at Austin.
GNU Lesser General Public License v3.0
Set the required system (boost or cython) by setting an environment variable with name MN_BUILD. Example in Linux:
then, the usual:
python setup.py build_ext python setup.py install