Reinforcement Learning

An Introduction

Nonfiction, Computers, Advanced Computing, Artificial Intelligence, General Computing
Cover of the book Reinforcement Learning by Richard S. Sutton, Andrew G. Barto, The MIT Press
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Richard S. Sutton, Andrew G. Barto ISBN: 9780262303842
Publisher: The MIT Press Publication: February 26, 1998
Imprint: A Bradford Book Language: English
Author: Richard S. Sutton, Andrew G. Barto
ISBN: 9780262303842
Publisher: The MIT Press
Publication: February 26, 1998
Imprint: A Bradford Book
Language: English

Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications.

Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.

The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications.

Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.

The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.

More books from The MIT Press

Cover of the book The Rhythmic Event by Richard S. Sutton, Andrew G. Barto
Cover of the book The Rediscovery of the Wild by Richard S. Sutton, Andrew G. Barto
Cover of the book Twelve Tomorrows by Richard S. Sutton, Andrew G. Barto
Cover of the book I of the Vortex by Richard S. Sutton, Andrew G. Barto
Cover of the book Applied Ethics in Mental Health Care by Richard S. Sutton, Andrew G. Barto
Cover of the book Applied State Estimation and Association by Richard S. Sutton, Andrew G. Barto
Cover of the book Tomorrow's Energy by Richard S. Sutton, Andrew G. Barto
Cover of the book Digital Lifeline? by Richard S. Sutton, Andrew G. Barto
Cover of the book Laboratory Lifestyles by Richard S. Sutton, Andrew G. Barto
Cover of the book Site Planning by Richard S. Sutton, Andrew G. Barto
Cover of the book The Dash—The Other Side of Absolute Knowing by Richard S. Sutton, Andrew G. Barto
Cover of the book The Techno-Human Condition by Richard S. Sutton, Andrew G. Barto
Cover of the book After Phrenology by Richard S. Sutton, Andrew G. Barto
Cover of the book Shanzhai by Richard S. Sutton, Andrew G. Barto
Cover of the book Blended Learning in Practice by Richard S. Sutton, Andrew G. Barto
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy