π Session structure β 15 minutes of recap (if second part of a chapter) β 60 minutes silent reading β 45 min discussion

π Join Meetup To get the most out of the sessions make sure to get the book, prepare for the session chapters and read a bit ahead if possible. That will serve as a good basis for an interactive and productive discussion. Join us on Slack for discussions #rl_book

π Book Info Book : Reinforcement learning, An introduction Author : Richard Sutton and Andrew Barto Publication : MIT Press

A physical copy of the book can be purchased e.g. on Amazon Link to book. Alternatively, the book is available as a pdf from the authors website: http://incompleteideas.net/index.html

π Part 1: Tabular Solution Methods Session #1 Introduction Session #2: Multi-armed Bandits Session #3: Finite Markov Decision Processes Session #4: Dynamic Programming (1) Session #5: Dynamic Programming (2) Session #6: Monte Carlo Methods (1) Session #7: Monte Carlo Methods (2) Session #8: Temporal-difference Learning (1) Session #9: Temporal-difference Learning (2) Session #10: n-step Bootstrapping (1) Session #11: n-step Bootstrapping (2) Session #12: Planning and Learning with Tabular methods (1) Session #13: Planning and Learning with Tabular methods (1)