README.md

Reinforcement Learning

Courses

In these courses, you will learn the foundations of Reinforcement Learning.

General Courses on Reinforcement Learning

1. Reinforcement Learning by David Silver - UCL
2. Reinforcement Learning - Stanford CS234
3. Reinforcement Learning - IIT-M CS230
4. Excursions in Reinforcement Learning - Mila
5. Supplementary Materials from Reinforcement Learning Book

Deep Reinforcement Learning

1. Deep RL Bootcamp
2. Deep Reinforcement Learning - UC Berkeley CS 285
3. Spinning up Deep RL - OpenAI

Imitation Learning

1. Imitation Learning for Robotics

Specialised Courses

1. Deep Multi-Task and Meta Learning
2. Trust Policy Optimisation series

Books

1. Reinforcement Learning: An Introduction, Sutton and Barto, 2nd Edition
2. Markov Decision Processes: Discrete Stochastic Dynamic Programming by Martin Puterman
3. Reinforcement Learning and Optimal Control by Dimitri Bertsekas
4. Grokking Deep Reinforcement Learining
5. Reinforcement Learning: Industrial Applications of Intelligent Agents

Clean Implementations

1. RL-Adventure and RL-Adventure2 by higgsfield
2. RLlib: Scalable Reinforcement Learning

Blog Posts/Tutorials

1. RL— Introduction to Deep Reinforcement Learning
2. Deep Reinforcement Series by Jonathan Hui
3. All the fantastic blogs by Lilian Weng
4. Debugging RL, Without the Agonizing Pain by Andy Jones
5. Variety of Introductory Blog Posts on RL

Research Papers

State of the art algorithms

1. Policy Gradient Methods for Reinforcement Learning with Function Approximation
2. Actor-Critic Algorithms
3. Playing Atari with Deep Reinforcement Learning
4. Deep Deterministic Policy Gradient
5. Asynchronous Methods for Deep Reinforcement Learning
6. Trust Region Policy Optimization
7. Proximal Policy Optimization Algorithms