MichalBortkiewicz/JaxGCRL

A framework for Reinforcement Learning research.

RL Environments in JAX 🌍

A benchmark for offline goal-conditioned RL and offline RL

SBX: Stable Baselines Jax (SB3 + Jax) RL algorithms

🕹️ A diverse suite of scalable reinforcement learning environments in JAX

Multi-Agent Reinforcement Learning with JAX

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

A library of reinforcement learning components and agents