Program learning to play Flappy Bird by machine learning (Neuroevolution)

Machine Learning for Flappy Bird using Neural Network and Genetic Algorithm

Python implementation of the NEAT neuroevolution algorithm

Evolutionary Algorithm using Python

A simple factor network implementation written by JavaScript

SharpNEAT - Evolution of Neural Networks. A C# .NET Framework.

Deprecated! See:

A neuroevolution game experiment.

Always sparse. Never dense. But never say never. A repository for the Adaptive Sparse Connectivity concept and its algorithmic instantiation, i.e. Sparse Evolutionary Training, to boost Deep Learning scalability on various aspects (e.g. memory and computational time efficiency, representation and generalization power).

Evolution Simulator with Box2D

A collection of Deep Neuroevolution resources or evolutionary algorithms applying in Deep Learning (constantly updating)

Evolving squids through neuroevolution

An Elixir Evolutive Neural Network framework à la G.Sher

Using tensorflow to build a population of models that trade crypto and breed/mutate iteratively

Neuroevolution Framework for Tensorflow 2.x focusing on modularity and high-performance. Preimplements NEAT, DeepNEAT, CoDeepNEAT, etc.

TensorFlow Eager implementation of NEAT and Adaptive HyperNEAT

Evolutionary Algorithms Framework

Pure Python Library for ES-HyperNEAT. Contains implementations of HyperNEAT and ES-HyperNEAT.

NEAT (NeuroEvolution of Augmenting Topologies) implemented in Go

This program evolves an AI using the NEAT algorithm to play Super Mario Bros.

A pytorch implementation of the NEAT (NeuroEvolution of Augmenting Topologies) algorithm

Radiate is a parallel genetic programming engine capable of evolving solutions to many problems as well as training learning algorithms.

EXONA: The Evolutionary eXploration of Neural Networks Framework -- EXACT, EXALT and EXAMM

Rust Neat - NeuroEvolution of Augmenting Topologies

The GOLang implementation of NeuroEvolution of Augmented Topologies (NEAT) method to grow and teach Artificial Neural Networks without back propagation

A public python implementation of the DeepHyperNEAT system for evolving neural networks. Developed by Felix Sosa and Kenneth Stanley. See paper here: https://eplex.cs.ucf.edu/papers/sosa_ugrad_report18.pdf

Python implementation of the NEAT neuroevolution algorithm

Applied artificial intelligence in Godot game engine

Neuroevolution in F#