> ## Documentation Index
> Fetch the complete documentation index at: https://docs.kalarislabs.com/llms.txt
> Use this file to discover all available pages before exploring further.

# stable-baselines3 — AI agent skill for data science and ml

> Production-ready reinforcement learning algorithms (PPO, SAC, DQN, TD3, DDPG, A2C) with scikit-learn-like API.

# `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.

**Category:** [data-science-and-ml](/research-agent-skills/skills#data-science-and-ml) · **License:** MIT · **Version:** 1.3

## Install

```bash theme={null}
npx research-agent-skills install stable-baselines3
npx skills add KalarisLabs/research-agent-skills --skill stable-baselines3
```

## When to use it

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.

## Full playbook

Read [SKILL.md](https://github.com/KalarisLabs/research-agent-skills/blob/main/skills/stable-baselines3/SKILL.md) for the complete workflow, references and any scripts. The agent installer copies the full skill folder.


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