Introduction to Reinforcement Learning

Pre-requisites:

None

Text Book:

• Reinforcement Learning: An Introduction by Richard S. Sutton and Andrew G. Barto, The MIT Press, 2nd edition, 2018. 

Course Syllabus Outline:

Introduction

Multi-armed Bandits

Finite Markov Decision Processes

Dynamic Programming

Monte Carlo Methods

Temporal-Difference Learning

Bootstrapping

Learning with Tabular Methods

On-Policy Prediction and Control with Approximation

Policy Gradient Methods

Lecture Resources:

- Mainly Classroom Notes

- More through Google Classroom [invitation based, exclusive to those who officially register]