Project Title
baselines — High-Quality Reinforcement Learning Algorithms Implementations
Overview
OpenAI Baselines is a collection of high-quality implementations of reinforcement learning algorithms designed to facilitate research and experimentation in the field. It provides a solid foundation for researchers to build upon, compare new approaches, and refine existing ones. The project aims to make it easier to replicate, refine, and identify new ideas in reinforcement learning.
Key Features
- Comprehensive set of reinforcement learning algorithms
- Supports TensorFlow versions from 1.4 to 1.14
- Easy-to-use command-line interface for training models
- MuJoCo physics simulator support for advanced simulations
Use Cases
- Researchers and developers in the field of machine learning and AI can use Baselines to experiment with and compare different reinforcement learning algorithms.
- Educational purposes, where students and instructors can utilize Baselines to understand the practical implementation of theoretical concepts in reinforcement learning.
- As a benchmarking tool for comparing the performance of new algorithms against established ones.
Advantages
- High-quality, well-maintained codebase that serves as a reliable starting point for research.
- Supports a wide range of TensorFlow versions, making it compatible with various projects.
- Provides a straightforward method for training and testing different algorithms with minimal setup.
Limitations / Considerations
- The project is in maintenance mode, which means it may not receive new features but will continue to receive bug fixes and minor updates.
- MuJoCo, which is used for some examples, is proprietary and requires a license, which might be a barrier for some users.
Similar / Related Projects
- Ray RLlib: A scalable reinforcement learning library that supports a variety of algorithms and is designed for distributed training, differing from Baselines in its focus on scalability.
- Stable Baselines3: A fork of Baselines that supports TensorFlow 2.x and aims to maintain the library with updates and new features, offering a more modern alternative.
- Gym: A toolkit for developing and comparing reinforcement learning algorithms, which complements Baselines by providing a standardized environment for testing.
Basic Information
- GitHub: https://github.com/openai/baselines
- Stars: 16,434
- License: Unknown
- Last Commit: 2025-09-15
📊 Project Information
- Project Name: baselines
- GitHub URL: https://github.com/openai/baselines
- Programming Language: Python
- ⭐ Stars: 16,434
- 🍴 Forks: 4,933
- 📅 Created: 2017-05-24
- 🔄 Last Updated: 2025-09-15
🏷️ Project Topics
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This article is automatically generated by AI based on GitHub project information and README content analysis