nguyensu/awesome-deep-rl

A curated list of awesome Deep Reinforcement Learning resources

Awesome Deep Reinforcement Learning

Table of Contents

• Courses
• Books
• Guides
• Guides
• Talks / Lectures
• Papers
• Blog Posts
• Video examples
• Code Examples
• Datasets
• Frameworks
• Contributing

Courses

1. Stanford’s CS234: Reinforcement Learning (2019)
   • Videos
2. DeepMind's Advanced Deep Learning & Reinforcement Learning (2018)
   • Videos
3. OpenAI's Spinning Up in Deep RL (2018)
4. Georgia Tech's CS 8803 Deep Reinforcement Learning (2018?)
5. UC Berkeley's CS294-112 Deep Reinforcement Learning (2018 Fall)
6. Thomas Simonini's Deep Reinforcement Learning Course 🕹️ (ongoing)
7. Deep RL Bootcamp (2017)
8. UC Berkeley's CS188 Intro to AI (2014)
9. Deep Mind (2015)
   • Slides
   • Videos

Books

• Reinforcement Learning: An Introduction by Richard S. Sutton and Andrew G. Barto (2017)
• Algorithms for Reinforcement Learning by Csaba Szepesvari (updated 2019)
• Deep Reinforcement Learning Hands-On by Maxim Lapan (2018)
  • book
  • code
• Deep Reinforcement Learning in Action by Alexander Zai and Brandon Brown (in progress)
• Grokking Deep Reinforcement Learning by Miguel Morales (in progress)

Guides

• 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
  • A Beginner's Guide to Deep Reinforcement Learning by skymind
  • http://www.argmin.net/2018/06/25/outsider-rl/
  • https://lilianweng.github.io/lil-log/2018/02/19/a-long-peek-into-reinforcement-learning.html
• 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
• 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

Talks

• Introduction to Deep Reinforcement Learning by Lex Fridman (2019)
  • slides
  • video
• Reinforcement Learning for the People and/or by the People by Emma Brunskill (2017)
  • slides
  • video
• Deep Reinforcement Learning by John Schulman (2016)
• Deep Robotic Learning by Sergey Levine (2017)

Papers

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
  • Technical paper
  • Technical blog post
  • [Nontechnical blog post])(https://databeta.wordpress.com/2018/09/20/the-crossroads-of-ai-and-database-algorithms-query-optimization/)

Blog Posts

• Deep Reinforcement Learning — Policy Gradients — Lunar Lander!
• Deep Reinforcement Learning: Pong from Pixels by Andrej Karpathy

Video examples

• DL Agent learning to play Atari
• Pong, Tic Tac Toe, and Super Mario with Deep Q-learning
• Miscellaneous robots learning

Code Examples

• 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
    • MDP
    • DP

Datasets

• MLPerf's benchmark suite for RL

Frameworks

• OpenAI's Gym: A toolkit for developing and comparing reinforcement learning algorithms
  • Overview
  • Code
• Google's Dopamine: A research framework for fast prototyping of reinforcement learning algorithms
  • Overview
  • Code

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Contributing

Have anything in mind that you think is awesome and would fit in this list? Feel free to send me a pull request!

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License

To the extent possible under law, Dr. Brian J. Spiering has waived all copyright and related or neighboring rights to this work.