• Title: Reinforcement Learning: An Introduction, Second Edition
• Author(s) Richard S. Sutton and Andrew G. Barto
• Publisher: MIT Press, Cambridge, MA, 2018; eBook (Creative Commons Licensed)
• License(s): CC BY-NC-ND 2.0
• Hardcover: 522 pages
• eBook: HTML and PDF (548 pages)
• Language: English
• ISBN-10: 0262039249
• ISBN-13: 978-0262039246
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Book Description

This book provides a clear and simple account of the field's key ideas and algorithms of Reinforcement Learning (RL).

Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. The treatment to be accessible to readers in all of the related disciplines.

This book is the bible of reinforcement learning, and the new edition is particularly timely given the burgeoning activity in the field. No one with an interest in the problem of learning to act - student, researcher, practitioner, or curious nonspecialist - should be without it.

• Richard S. Sutton is a Canadian computer scientist and a Professor of Computing Science and AITF Chair in Reinforcement Learning and Artificial Intelligence at the University of Alberta, and also Distinguished Research Scientist at DeepMind.

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• Amazon (1st Edition)

• Machine Learning
• Neural Networks and Depp Learning
• Artificial Intelligence
• Statistics, Mathematical Statistics, and SAS Programming
• Probability and Stochastic Processe

• Reinforcement Learning: An Introduction, Second Edition (Richard S. Sutton, et al)
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