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Reinforcement Learning Resources

A curated list of awesome reinforcement courses, video lectures, books, library and many more.

Table of Contents

Free Books

  1. Reinforcement Learning: An Introduction 1st Ed by Richard Sutton and Andrew Barto
  2. Reinforcement Learning: An Introduction 2nd Edition, in progress by Richard Sutton and Andrew Barto
  3. Algorithms for Reinforcement Learning by Csaba Szepesvari
  4. Artificial Intelligence: Foundations of Computational Agents by David Poole and Alan Mackworth

Courses

  1. 10703: Deep Reinforcement Learning and Control, Spring 2017
  2. Reinforcement Learning
  3. Practical Reinforcement Learning
  4. Reinforcement Learning Explained
  5. Practical Reinforcement Learning

Videos and Lectures

  1. COMPM050/COMPGI13 Reinforcement Learning
  2. CS294 Deep Reinforcement Learning
  3. CS229 Machine Learning - Lecture 16: Reinforcement Learning
  4. Deep RL Bootcamp
  5. Lecture 2: Deep Reinforcement Learning for Motion Planning
  6. Lecture 8: Markov Decision Processes 1
  7. Lecture 9: Markov Decision Processes 2
  8. Lecture 10: Reinforcement Learning 1
  9. Lecture 11: Reinforcement Learning 2
  10. MIT 6.S191: Reinforcement Learning

Papers

  1. Generalization in Reinforcement Learning: Successful examples using sparse coding, Richard S. Sutton
  2. Learning from Delayed Rewards, Christopher J. C. H. Watkins
  3. Learning to predict by the methods of temporal differences, Richard S. Sutton
  4. Learning from Delayed Rewards, Cambridge, Chris Watkins
  5. Monte Carlo Inversion and Reinforcement Learning, Andrew Barto, Michael Duff
  6. Reinforcement Learning with Replacing Eligibility Traces, Machine Learning, Satinder P. Singh, Richard S. Sutton

Tutorials

  1. Reinforcement Learning
  2. Reinforcement Learning Tutorial
  3. Let’s make a DQN: Implementation
  4. Simple Reinforcement Learning with Tensorflow Part 4: Deep Q-Networks and Beyond

Sample Code

  1. Reinforcement Learning: An Introduction (2nd Edition)

Libraries

  1. OpenAI gym
  2. OpenAI Retro
  3. Deep Mind Lab
  4. RL-Library
  5. RL Lab

Contributing

Jika anda ingin berkontribusi dalam github ini, sangat disarankan untuk Pull Request namun dengan resource berbahasa indonesia.