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The Holy Book of reinforcement learning - Sutton & Barto - Reinforcement Learning: An Introduction - 2nd Edition
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UCL Lectures - David Silver (Head of Reinforcement Learning at DeepMind) - slides - lecture videos
For neural networks - Deep Learning - Ian Goodfellow, Yoshua Bengio and Aaron Courville
For everything else (linear models, random forests etc)
- Elements of Statistical Learning - Trevor Hastie, Robert Tibshirani and Jerome Friedman
- Pattern Recognition and Machine Learning - Christopher M. Bishop
The Long-term of AI & Temporal-Difference Learning (Richard Sutton - DeepMind)
Deep Reinforcement Learning (John Schulman - Open AI & Berkley)
Deep Reinforcement Learning (Pieter Abbeel - Open AI & Berkley)
Deep Reinforcement Learning (David Silver - DeepMind & UCL)
Deep Reinforcement Learning and Real World Challenges (Raia Hadsell - DeepMind)
Deep Reinforcement Learning in TensorFlow (Danijar Hafner - Stanford)
2017 NIPS David Silver Keynote - AlphaZero
A History of Reinforcement Learning - Prof. A.G. Barto
CS 294: Deep Reinforcement Learning, Fall 2017 - Sergey Levine - Berkley - course materials - lecture videos
CS 598: Statistical Reinforcement Learning - Nan Jiang - Illinois - course materials
A (Long) Peek into Reinforcement Learning - blog post
Practical RL - course in reinforcement learning in the wild - repo
- Lecture 1 - Motivation + Overview + Exact Solution Methods - Pieter Abbeel
- Lecture 2 - Sampling-based Approximations and Function Fitting - Yan (Rocky) Duan
- Lecture 3 - Deep Q-Networks - Vlad Mnih
- Lecture 4a - Policy Gradients - John Schulman
- Lecture 4b - Policy Gradients Revisited - Andrej Karpathy
- Lecture 5 - Natural Policy Gradients, TRPO, PPO - John Schulman
- Lecture 6 - Nuts and Bolts of Deep RL Experimentation - John Schulman
- Lecture 7 - SVG, DDPG, and Stochastic Computation Graphs - John Schulman
- Lecture 8 - Derivative Free Methods - Xi (Peter) Chen
- Lecture 9 - Model-based Reinforcement Learning - Chelsea Finn
- Lecture 10a - Utlities - Pieter Abbeel
- Lecture 10b - Inverse Reinforcement Learning - Chelsea Finn
- Frontiers Lecture I - Recent Advances, Frontiers and Future of Deep RL - Vlad Mnih-
- Frontiers Lecture II: Recent Advances, Frontiers and Future of Deep RL - Sergey Levine
Deep Reinforcement Learning: Pong from Pixels
Deep Deterministic Policy Gradients in TensorFlow
Open AI gym - environments - repo - paper
Open AI baselines - agents - repo
Berkley's rllab - agents & environments - repo
Intel's coach - agents & environments - repo - blog post
unity - 3D environments - github - paper
Dopamine - Rainbow implementation - github - blog post
Holodeck - Unity 3D environments - github - blog post
RLenv.directory - directory of reinforcement learning environments
Horizion - Facebook platform for applied RL - github - paper - blog post