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 provides coverage of material from the Reinforcement Learning MOOC, taught by Adam White and Martha White, as well as content from the University of Alberta's courses CMPUT 655, instructed by Michael Bowling and Simone Parisi, and CMPUT 365, where I serve as a teaching assistant under Marlos C. Machado.

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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.