sk Skill · dralkh
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.
Open on skills.sh ↗read 2026-09-18
- installs 8w
- 0
- 30-day movement
- starts with the next reading
- Related entries
- 3
- Connections
- 1
pythonbashTypeScript
- Host repository
- dralkh/iktinah
- Version
- 1.1
- Allowed tools
- Read Write Edit Bash
- Compatible with
- Requires Python 3.10+, PyTorch >= 2.3, and stable-baselines3 2.8+. Gymnasium environments, optional extras for TensorBoard and Atari (ale-py).
- Licence
- MIT license
- Host stars
- 78
- Host language
- TypeScript