stable-baselines3
Production-ready reinforcement learning algorithms (PPO, SAC, DQN, TD3, DDPG, A2C) with scikit-learn-like API. Use for standard RL experiments, quick prototyping, and well-documented algorithm implementations. Best for single-agent RL with Gymnasium environments. For high-performance parallel training, multi-agent systems, or custom vectorized environments, use pufferlib instead.
Details
- Path
- skills/stable-baselines3
- License
- MIT license
- Allowed tools
- 1
- Bundled scripts
- 3
- Dependencies
- 3
Allowed tools
Read Write Edit Bash
Bundled scripts
- skills/stable-baselines3/scripts/evaluate_agent.py
- skills/stable-baselines3/scripts/train_rl_agent.py
- skills/stable-baselines3/scripts/custom_env_template.py