imitation (HumanCompatibleAI)
Clean implementations of behavioral cloning, DAgger, GAIL, AIRL and more for imitation learning research.
Reliable RL algorithm implementations (PPO, SAC, …) widely used before specialized robot trainers.
Why: Default reliable RL baselines for many robot students
Stable-Baselines3 (SB3) is the default reliable implementation of standard RL algorithms (PPO, SAC, TD3, DQN, …) for many students entering robot learning. It is not robot-specific, but it is the cleanest way to learn on-policy / off-policy loops before specialized stacks like rsl_rl or Isaac Lab trainers.
Pair SB3 with Gymnasium / Gymnasium-Robotics or simple MuJoCo tasks first. Once you need massive parallel locomotion or GPU envs, graduate to robot-native trainers.
On this hub’s Learning Path, SB3 sits in Foundations: get one training curve and one evaluation rollout working before touching VLAs.
Researchers, students, and builders comparing open embodied stacks.
pip
pip install stable-baselines3[extra]
Best generic RL algorithms package; use rsl_rl for high-throughput locomotion.
Clean implementations of behavioral cloning, DAgger, GAIL, AIRL and more for imitation learning research.
Content reviewed 2026-07-28