- Courses
- Books
- Guides
- Frameworks
- Talks / Lectures
- Papers
- Blog Posts
- Code Examples
- Datasets
- Contributing
- DeepMind's Advanced Deep Learning & Reinforcement Learning (2018)
- OpenAI's Spinning Up in Deep RL (2018)
- Georgia Tech's CS 8803 Deep Reinforcement Learning
- Stanford’s CS234: Reinforcement Learning (2018)
- UC Berkeley's CS294-112 Deep Reinforcement Learning (2018 Fall)
- Thomas Simonini's Deep Reinforcement Learning Course 🕹️ (ongoing)
- Deep RL Bootcamp (2017)
- UC Berkeley's CS188 Intro to AI (2014)
- Deep Mind (2015)
- Algorithms for Reinforcement Learning by Csaba Szepesvari (2009)
- Reinforcement Learning: An Introduction by Richard S. Sutton and Andrew G. Barto (2017)
- Deep Reinforcement Learning Hands-On by Maxim Lapan (2018)
- Deep Reinforcement Learning in Action by Alexander Zai and Brandon Brown (in progress)
- Grokking Deep Reinforcement Learning by Miguel Morales (in progress)
- Related awesome guides
- awesome-rl #1
- awesome-rl #2
- awesome-deep-rl: Inspiring but too focused on specific implementations
- awesome-rl-nlp: NLP for the win
- Complete guides
- Short introductions
- A Medium Series
- https://medium.com/@m.alzantot/deep-reinforcement-learning-demystified-episode-0-2198c05a6124
- https://becominghuman.ai/genetic-algorithm-for-reinforcement-learning-a38a5612c4dc
- https://medium.com/@m.alzantot/deep-reinforcement-learning-demysitifed-episode-2-policy-iteration-value-iteration-and-q-978f9e89ddaa
- A Medium Series
- https://github.com/andri27-ts/60_Days_RL_Challenge
- https://github.com/jachiam/rl-intro
- http://planspace.org/20170830-berkeley_deep_rl_bootcamp/
- https://github.com/google/dopamine
- OpenAI's Gym: A toolkit for developing and comparing reinforcement learning algorithms
- Google's Dopamine: A research framework for fast prototyping of reinforcement learning algorithms
- Deep Reinforcement Learning by John Schulman (2016)
OpenAI's Key Papers in Deep RL
Survey:
- Deep Reinforcement Learning: An Overview (2018)
- A Brief Survey of Deep Reinforcement Learning (2017)
Results:
- Learning to Optimize Join Queries With Deep Reinforcement Learning
- DL Agent learning to play Atari
- Pong, Tic Tac Toe, and Super Mario with Deep Q-learning
- Miscellaneous robots learning
- OpenAI Baselines: A set of high-quality implementations of reinforcement learning algorithms
- Mingo: An open-source implementation of the AlphaGoZero algorithm
- Adventures with Sutton and Barto
- Python implementation
- Rendered Jupyter Notebooks
Have anything in mind that you think is awesome and would fit in this list? Feel free to send me a pull request!
To the extent possible under law, Dr. Brian J. Spiering has waived all copyright and related or neighboring rights to this work.