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

Simple and easily configurable grid world environments for reinforcement learning

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

Reinforcement Learning environments based on the 1993 game Doom

A collection of robotics simulation environments for reinforcement learning

Clean PyTorch implementations of imitation and reward learning algorithms

A standard format for offline reinforcement learning datasets, with popular reference datasets and related utilities

Multi-objective Gymnasium environments for reinforcement learning

Modular Reinforcement Learning (RL) library (implemented in PyTorch, JAX, and NVIDIA Warp) with support for Gymnasium/Gym, NVIDIA Isaac Lab, MuJoCo Playground and other environments

Reinforcement Learning environments for Traffic Signal Control with SUMO. Compatible with Gymnasium, PettingZoo, and popular RL libraries.

A fork of gym-retro with additional games, emulators and supported platforms

PettingZoo and Gymnasium bindings for popular reinforcement learning environments outside of Farama

Gymnasium environments for NES Mario games, with task metadata, reward instrumentation, and reproducible evaluation interfaces.

Unified Reinforcement Learning Framework

An open harness to simulate and deploy PX4/ArduPilot/Betaflight perception-based drone swarms with ROS2, YOLO, NVIDIA Jetson

Multi-Objective Reinforcement Learning algorithms implementations.

Base Mujoco Gymnasium environment for easily controlling any robot arm with operational space control. Built with dm-control PyMJCF for easy configuration.

Native C++ NES emulator with Python/Gymnasium APIs, vector execution, and cross-platform packaging.

Model Predictive Path Integral Control (MPPI) with PyTorch

Readable single-file PyTorch implementations of deep RL algorithms: DQN, PPO, SAC, TD3, DDPG and A2C, with Gymnasium and Atari support plus W&B tracking.