# openai/spinningup

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11,812 stars · 2,454 forks · Python · MIT

## Links

- GitHub: https://github.com/openai/spinningup
- Homepage: https://spinningup.openai.com/
- awesome-repositories: https://awesome-repositories.com/repository/openai-spinningup.md

## Description

Spinning Up is a deep reinforcement learning curriculum designed to teach the theory and implementation of deep reinforcement learning algorithms. It serves as a guided educational resource for understanding how agents interact with environments through mathematical models and code.

The project provides a research roadmap consisting of a curated collection of influential research papers and theoretical concepts. This literature study is designed to guide a deeper exploration of specific reinforcement learning domains.

The curriculum covers the implementation of reinforcement learning logic through standalone code examples and a study of core terminology and theoretical foundations.

## Tags

### Education & Learning Resources

- [Structured Reinforcement Learning Curricula](https://awesome-repositories.com/f/education-learning-resources/educational-resources/courses-training-certifications/courses-structured-learning/computer-science-curricula/educational-curriculum-repositories/structured-reinforcement-learning-curricula.md) — Ships a structured educational curriculum covering mathematical concepts and algorithms for reinforcement learning.
- [Algorithm Implementations](https://awesome-repositories.com/f/education-learning-resources/algorithm-implementations.md) — Provides clean, readable educational implementations of reinforcement learning algorithms to demonstrate their mathematical foundations. ([source](https://github.com/openai/spinningup/blob/master/readme.md))
- [Reinforcement Learning Curricula](https://awesome-repositories.com/f/education-learning-resources/deep-learning-curriculum/reinforcement-learning-curricula.md) — Serves as a guided educational resource for learning both the theory and implementation of deep RL.
- [Implementation Guides](https://awesome-repositories.com/f/education-learning-resources/educational-resources/algorithms-theory-academics/algorithm-data-structure-guides/algorithm-guides/implementation-guides.md) — Provides code examples and mathematical models that demonstrate agent interaction with environments.
- [Reinforcement Learning Theory](https://awesome-repositories.com/f/education-learning-resources/reinforcement-learning-theory.md) — Offers a study of core reinforcement learning terminology and theoretical concepts. ([source](https://github.com/openai/spinningup/blob/master/readme.md))
- [Research Roadmaps](https://awesome-repositories.com/f/education-learning-resources/technical-roadmaps/phd-research-roadmaps/research-roadmaps.md) — Includes a research roadmap consisting of a curated collection of influential RL papers and concepts.

### Artificial Intelligence & ML

- [Educational Implementations](https://awesome-repositories.com/f/artificial-intelligence-ml/reinforcement-learning-algorithms/reinforcement-learning-simulators/educational-implementations.md) — Provides standalone code examples to help learners understand how reinforcement learning agent models are implemented.
- [Research Papers](https://awesome-repositories.com/f/artificial-intelligence-ml/research-papers.md) — Provides a curated collection of influential research papers in the field of reinforcement learning. ([source](https://github.com/openai/spinningup/blob/master/readme.md))