Materials for the introductory reinforcement learning course A Glance at Reinforcement Learning. I also maintain a curated collection of reinforcement learning resources in the rl-resources repo.
This project is built and maintained by Adam Green - email@example.com.
brew install node npm install npm start
- background statistical concepts
- Markov Decision processes
- value function methods (DQN and it's extensions)
- policy gradient methods
- AlphaGo to AlphaZero
- practical advice for experiments
- current state of the art
Goals for the course
Introduction to concepts, ideas and terminology. Familiarity with important literature. Understanding of the state of the field today. Practical strategies to run reinforcement learning experiments.
Where to go next
- The Holy Book of reinforcement learning - Sutton & Barto - Reinforcement Learning: An Introduction - 2nd Edition
- UCL Lectures - David Silver (Head of Reinforcement Learning at DeepMind) - slides - lecture videos
Further resources (video lectures, blog posts etc) are listed in dsr-rl/resources.md.