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PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
A standard API 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)
Self hosted FLOSS fitness/workout, nutrition and weight tracker
A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
C++-based high-performance parallel environment execution engine (vectorized env) for general RL environments.
Evaluate and improve models and agents using environments
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