RL.md

Reinforcement Learning (RL) Resources

Lectures

• Introduction to Reinforcement Learning

  • Instructor: Prof. David Silver (UCL)
  • Date: 2015
  • Playlist: Youtube
  • Additional
    • Site: slides, video available
  • Comments

• Reinforcement Learning Lecture Series 2018

  • Instructor: Hado van hasselt (Google DeepMind)
  • Date: 2018
  • Additional
    • site: video available

• CS234: Reinforcement Learning

  • Instructor: Prof. Emma Brunskill (Stanford)
  • Date: up to date
  • Playlist: Youtube (Winter 2019)
  • Additional
    • site: slides, assignment available
  • Comments

• CS285: Deep Reinforcement Learning

  • Instructor: Prof. Sergey Levine (UC Berkeley)
  • Date: up to date
  • Playlist: Youtube (Fall 2020)
  • Additional
    • site: slides, assignment available

• Reinforcement Learning and Optimal Control

  • Instructor: Prof. Dimitri P. Bertsekas (MIT)
  • Additional:
    • site: slides, video available
    • has companion book (Reinforcement learning and optimal control)

• Reinforcement Learning Specialization

  • Instructor: Martha White & Adam White (University of Alberta)
  • Additional:

    • site: video and assignment available

    • Consists of three lectures & Capstone project

      • Fundamentals of Reinforcement Learning
      • Sample-based Learning Methods
      • Predictions and Control with Function Approximation
      • A Complete Reinforcement Learning System

    • You can also take the lecture by audit (no assignment)

Books

• Reinforcement Learning: An Introduction (2nd edition)

  • Author: Andrew Barto and Richard S. Sutton
  • Date: 2018
  • Available: paperback, E-book (free)
  • Comments
    • Base reference book in reinforcement learning
    • Companion lecture on Coursera

• Reinforcement Learning and Optimal Control

  • Author: Dimitri P. Bertsekas (MIT)
  • Date: 2019
  • Available: paperback

• Algorithms of Reinforcement Learning

  • Author: Csaba Szepesvári
  • Date: 2010
  • Available: paperback, E-book
  • Companion site (free)

• Bandit Algorithms

  • Author: Tor Lattimore, Csaba Szepesvári
  • Date: 2020
  • Available: paperback, E-book (free)
  • Companion site

• Grokking Deep Reinforcement Learning

  • Author: Miguel Morales
  • Date: 2020
  • Available: paperback, E-book
  • Examples: github

Web resources

• Deep RL Bootcamp

  • Organization: Pieter Abbeel et al.
  • Date: Aug. 2017
  • Addtional
    • site: slides, video, assignment available

• Theory of Reinforcement Learning Boot Camp

  • Organization: Simons Institute (UC Berkeley)
  • Date: Sep. 2020
  • Additional
    • site: video available

• Reinforcement Learning Summer School 2018

  • Organization: CIFAR, Vector Institute, AMII, MILA
  • Date: 2018
  • Additional
    • site: slides, video available

• OpenAI Spinning Up

  • Organization: Josh Achiam (OpenAI)
  • Date: up to date
  • Additional
    • site: reading, assignment available

• Reinforcement Learning Day 2019

  • Organization: Microsoft Research
  • Date: Oct. 2019
  • Additional
    • site: slides, video available