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stable-baselines3

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Python

Project Description

PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

stable-baselines3: PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

Project Title

stable-baselines3 — Reliable PyTorch Implementations of Reinforcement Learning Algorithms

Overview

Stable Baselines3 (SB3) is a set of reliable implementations of reinforcement learning algorithms in PyTorch, designed to facilitate research and industry applications. It offers a common interface for various algorithms, making it easier to replicate, refine, and identify new ideas in the field of reinforcement learning.

Key Features

  • State of the art RL methods
  • Comprehensive documentation
  • Support for custom environments and policies
  • Dict observation space support
  • Ipython / Notebook friendly
  • Tensorboard support
  • PEP8 code style adherence
  • Custom callback functionality
  • High code coverage
  • Type hints for better code quality

Use Cases

  • Researchers and data scientists using reinforcement learning for experiments and model development.
  • Industry professionals implementing reinforcement learning solutions in production environments.
  • Educators and students learning about reinforcement learning through practical applications.

Advantages

  • Provides a common interface for various reinforcement learning algorithms, simplifying experimentation.
  • Offers extensive documentation and resources for beginners to get started with RL.
  • Supports a wide range of features, including custom environments, policies, and callbacks, enhancing flexibility.

Limitations / Considerations

  • Assumes some knowledge of Reinforcement Learning; not recommended for absolute beginners without practice.
  • The library is focused on PyTorch, which may not be suitable for those preferring other frameworks.

Similar / Related Projects

  • Stable Baselines: The predecessor to SB3, implemented in TensorFlow. SB3 offers PyTorch implementations and a more modern approach.
  • OpenAI Baselines: A set of high-quality implementations of reinforcement learning algorithms. SB3 focuses on PyTorch and provides a more streamlined interface.
  • Gym: A toolkit for developing and comparing reinforcement learning algorithms. SB3 can be used in conjunction with Gym for training and testing RL models.

Basic Information


📊 Project Information

🏷️ Project Topics

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📚 Documentation


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Project Information

Created on 5/5/2020
Updated on 9/15/2025