Intro to Reinforcement Learning #3 (APAC)

📌 Book Reading & Discussion
📌 Session #3: Finite Markov Decision Processes

In this RL series we will cover "Reinforcement learning: An introduction" by Richard Sutton and Andrew Barto.

Session leads: Pierre Wüthrich, Emil Vatai, Anugraha Sinha

📌 Session structure
● 60 minutes silent reading
● 45 min discussion

📌 Join Zoom Meeting
https://us02web.zoom.us/j/87317775722

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

●● 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 author's website: http://incompleteideas.net/index.html

Session #1 Introduction

● Part 1: Tabular Solution Methods
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)

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