This repository explores the use of OpenAI's Gym Retro and NEAT (NeuroEvolution of Augmenting Topologies) in Python to train AI agents to play classic games.
The aim of this project is to utilize Gym Retro, an environment for reinforcement learning that allows the training of agents in retro game environments, along with the NEAT algorithm, to create AI agents capable of playing classic games.
Inspiration for this project comes from Lucas Thompson, a content creator known for exploring similar topics on his YouTube channel.
- Integration of Gym Retro for classic game environments.
- Utilization of NEAT (NeuroEvolution of Augmenting Topologies) for training AI agents.
- Includes sample code and experiments for training AI to play classic games.