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This is the homepage of the course CMPUT 653: Theoretical Foundations of Reinforcement Learning taught by Csaba Szepesvári at the University of Alberta in the Winter semester of 2021.

Additional information and resources can be accessed from the sidepane on the left. The main website pages are under the heading Pages and the course notes (to come later) are organized under the heading Notes.

For inspiration, below is an illustrated guide to learning absolutely nothing by Eugene Vinitsky.


While students who want to know everything about RL will indeed face this vicious cycle, this course will be mostly self-contained. You only need to be able to follow (and want to follow!!!) proofs in calculus, linear algebra and probability theory. Detailed pre-requisites are here.