Introduction to Reinforcement Learning

This documentation is designed to be an additional resource for students and a reliable, interactive knowledge base for anyone interested in reinforcement learning (RL).

It covers the Reinforcement Learning MOOC by professors Adam and Martha White, as well as additional content from the University of Alberta's CMPUT 655 and CMPUT 365 courses, the latter of which I am a teaching assistant.

warning

For a more comprehensive understanding of the topics covered, I highly recommend the textbook Reinforcement Learning: An Introduction by Sutton and Barto, and checking out the MOOC.

References

Reinforcement Learning: An Introduction by Sutton and Barto.
Reinforcement Learning MOOC by professors Adam and Martha White.
Foundations of Deep RL video series by professor Pieter Abbeel.
UC Berkeley - CS 285: Deep RL, 2023 lectures by professor Sergey Levine.
DeepMind x UCL - Introduction to Reinforcement Learning, 2015 lectures by professor David Silver.
UofA - CMPUT 365: Introduction to Reinforcement Learning, 2023 lectures and worksheets by professor Csaba Szepesvári.