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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.
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
Evaluate and improve models and agents using environments