Popular GitHub Repositories for Gym Env

FinRL: Financial Reinforcement Learning. ?

PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

An API standard for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)

High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

Reinforcement Learning / AI Bots in Card (Poker) Games - Blackjack, Leduc, Texas, DouDizhu, Mahjong, UNO.

An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities

A minimalist environment for decision-making in autonomous driving

MuZero

A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.

Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms

The most simple, flexible, and comprehensive OpenAI Gym trading environment (Approved by OpenAI Gym)

Rainbow is all you need! A step-by-step tutorial from DQN to Rainbow

Reinforcement Learning environments based on the 1993 game Doom :godmode:

PyBullet Gymnasium environments for single and multi-agent reinforcement learning of quadcopter control

Humanoid-Gym: Reinforcement Learning for Humanoid Robot with Zero-Shot Sim2Real Transfer https://arxiv.org/abs/2404.05695

[ICML 2017] TensorFlow code for Curiosity-driven Exploration for Deep Reinforcement Learning

[NeurIPS 2023 Spotlight] LightZero: A Unified Benchmark for Monte Carlo Tree Search in General Sequential Decision Scenarios (awesome MCTS)

High-quality single-file implementations of SOTA Offline and Offline-to-Online RL algorithms: AWAC, BC, CQL, DT, EDAC, IQL, SAC-N, TD3+BC, LB-SAC, SPOT, Cal-QL, ReBRAC

Proximal Policy Optimization (PPO) algorithm for Super Mario Bros

A collection of 100+ pre-trained RL agents using Stable Baselines, training and hyperparameter optimization included.