Reinforcement Learning – An Introduction (Adaptive Computation and Machine Learning series) - Hardcover
Synopsis
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.
"synopsis" may belong to another edition of this title.
About the Authors
Richard S. Sutton is 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.
Andrew G. Barto is Professor Emeritus in the College of Computer and Information Sciences at the University of Massachusetts Amherst.
"About this title" may belong to another edition of this title.
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Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning)
Published by
Bradford Books (edition First Edition), 1998
ISBN 10: 0262193981
ISBN 13: 9780262193986
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Hardcover
First Edition
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Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning)
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Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning) (Adaptive Computation and Machine Learning series)
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Hardcover. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority! Seller Inventory # S_453245387
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Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning)
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hardcover. Condition: Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority! Seller Inventory # S_457084918
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Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning)
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Reinforcement Learning
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MIT Press, Cambridge, MA, 1998
ISBN 10: 0262193981
ISBN 13: 9780262193986
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Hardcover
Seller: Sekkes Consultants, North Dighton, MA, U.S.A.
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Hardcover. Condition: Near fine. Dust Jacket Condition: Near fine. 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. InReinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. The only necessary mathematical background is familiarity with elementary concepts of probability. Owner Signature on ffep, fine otherwise. 7¼" - 9¼". Book. Seller Inventory # 278286
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Reinforcement Learning An Introduction (Adaptive Computation and Machine Learning Series)
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Condition: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. Dust jacket in fair condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,900grams, ISBN:9780262193986. Seller Inventory # 4315703
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Reinforcement Learning An Introduction (Adaptive Computation and Machine Learning Series)
Seller: Anybook.com, Lincoln, United Kingdom
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Condition: Fair. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In fair condition, suitable as a study copy. Dust jacket in fair condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,900grams, ISBN:9780262193986. Seller Inventory # 4315704
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£ 48.01
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Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning)
Published by
Bradford Books, 1998
ISBN 10: 0262193981
ISBN 13: 9780262193986
Used
Hardcover
First Edition
Seller: ReviBlio, Barcelona, B, Spain
Seller rating 5 out of 5 stars
Condition: 15 pages with some highlighted text, the rest excellent. The book provides a clear and simple account of the key ideas and algorithms in this area of artificial intelligence, where an agent learns to maximize a cumulative reward by interacting with a complex, uncertain environment. It covers the history of the field's intellectual foundations and proceeds to the core algorithms and concepts, including: The Reinforcement Learning Problem framed in terms of Markov Decision Processes (MDPs). Basic Solution Methods like Dynamic Programming, Monte Carlo methods, and the influential Temporal-Difference (TD) learning (e.g., Q-learning and SARSA). Function Approximation for handling large state spaces, including the use of artificial neural networks. More advanced topics like policy-gradient methods and a discussion of RL's relationships to psychology and neuroscience. Often referred to as the "bible" of the field, it is a foundational text suitable for students, researchers, and practitioners with a basic understanding of probability. Seller Inventory # ABE-1760107744142
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Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning)
Seller: YESIBOOKSTORE, MIAMI, FL, U.S.A.
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hardcover. Condition: As New. Seller Inventory # 0262193981-VB