Project Title

dopamine — A Research Framework for Rapid Prototyping of Reinforcement Learning Algorithms

Overview

Dopamine is a research framework designed for fast prototyping of reinforcement learning algorithms. It stands out for its compact, reliable codebase that facilitates easy experimentation and flexible development, allowing users to freely experiment with speculative research ideas. The framework is built to be reproducible, following the recommendations by Machado et al. (2018), and supports various agents implemented with JAX.

Key Features

Easy experimentation with benchmark experiments
Flexible development for trying out research ideas
Compact and reliable implementations of battle-tested algorithms
Reproducibility in results, adhering to scientific standards
Support for TensorFlow (legacy) and JAX (actively maintained) agents

Use Cases

Researchers and developers prototyping new reinforcement learning algorithms
Academics needing a reliable framework for reproducibility in their experiments
Companies exploring speculative research in reinforcement learning

Advantages

Small and easily grokked codebase for quick understanding and modification
Battle-tested algorithms for a solid starting point in research
JAX support for modern, high-performance computing
Docker containers for easy setup and use

Limitations / Considerations

The framework is not an official Google product, which may affect support and updates
Legacy TensorFlow support may become deprecated in favor of JAX
The framework is designed for research, which may not be suitable for production environments without further development

TensorFlow Agents: A library for reinforcement learning that integrates with TensorFlow, offering a different set of tools and algorithms.
Ray RLlib: A scalable reinforcement learning library that supports a variety of algorithms and is designed for distributed training.
Stable Baselines3: A set of improved implementations of reinforcement learning algorithms that build upon Stable Baselines, offering a different range of algorithms and features.

Basic Information

GitHub: https://github.com/google/dopamine
Stars: 10,806
License: Unknown
Last Commit: 2025-09-18

📊 Project Information

Project Name: dopamine
GitHub URL: https://github.com/google/dopamine
Programming Language: Jupyter Notebook
⭐ Stars: 10,806
🍴 Forks: 1,392
📅 Created: 2018-07-26
🔄 Last Updated: 2025-09-18

🏷️ Project Topics

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📚 Documentation

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dopamine

Project Description