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

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

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

👨‍💻 Gym & Club Management System https://gymie.in

👨‍💻 Gym & Club Management System https://gymie.in

A custom MARL (multi-agent reinforcement learning) environment where multiple agents trade against one another (self-play) in a zero-sum continuous double auction. Ray [RLlib] is used for training.

Framework and toolkits for building and evaluating collaborative agents that can work together with humans.

K-Sim Gym: Making robots useful with RL. Built on top of K-Sim.

Jiminy: a fast and portable Python/C++ simulator of poly-articulated robots with OpenAI Gym interface for reinforcement learning

A customized gym environment for developing and comparing reinforcement learning algorithms in crypto trading.

Set of robotic environments based on PyBullet physics engine and gymnasium.

A collection of multi agent environments based on OpenAI gym.