Reinforcement Learning: An Introduction

This second edition of 'Reinforcement Learning: An Introduction' by Richard S. Sutton and Andrew G. Barto provides a clear and simple account of the field's key ideas and algorithms.

The book is significantly expanded and updated, including new topics such as artificial neural networks, the Fourier basis, and expanded treatment of off-policy learning and policy-gradient methods.

It also includes new chapters on the relationships between reinforcement learning and psychology/neuroscience, as well as updated case studies on AlphaGo, AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy.

The final chapter discusses the future societal impacts of reinforcement learning.