DQN-Atari-Agents
The repository provides a detailed framework for training advanced DQN models, including DDQN, Dueling DDQN, and Rainbow. It features enhancements such as Noisy layer and Prioritized Experience Replay, supporting training from raw pixels or RAM data. With multiprocessing capabilities, users can experience expedited training through parallel environment setups. Benefit from adjustable agent options and customizable parameters to enhance performance in Atari games, while tracking progress using Tensorboard. This setup is perfect for developing expertise in reinforcement learning with modular adjustments.
