Agens stable_baselines3

skill_id: stable_baselines3 name: stable-baselines3 description: 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. version: 1.0.0 author: K-Dense Inc. license: MIT license tags:

• scientific-agent-skills
• stable-baselines3 tools: [] permissions: network: true filesystem: false shell: false agents:
• executor_agent enabled: true source: scientific-agent-skills entrypoint: entry.py readme: README.md input_schema: {} output_schema: type: object metadata: upstream_repo: K-Dense-AI/scientific-agent-skills upstream_skill: stable-baselines3 upstream_path: scientific-skills/stable-baselines3/SKILL.md upstream_frontmatter: name: stable-baselines3 description: 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. license: MIT license metadata: skill-author: K-Dense Inc.