The GOLang implementation of NeuroEvolution of Augmented Topologies (NEAT) method to evolve and train Artificial Neural Networks without error back propagation

This project provides GOLang implementation of Neuro-Evolution of Augmenting Topologies (NEAT) with Novelty Search optimization aimed to solve deceptive tasks with strong local optima

This is a neuro-evolution of augmenting topologies library. It uses a genetic algorithm to evolve neural networks. This is useful when you don't have a dataset to train your neural network, for example when you need an agent to interact with an environment or to learn to play some games.