The GOLang implementation of NeuroEvolution of Augmented Topologies (NEAT) method to evolve and train Artificial Neural Networks without error back propagation
Currently the mutation and reproduction logic encapsulated into Genome and Population. We need to extract it into Interfaces with concrete implementations to make code more clear.
Currently the mutation and reproduction logic encapsulated into Genome and Population. We need to extract it into Interfaces with concrete implementations to make code more clear.