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HPB-Red, Dallas, TX, U.S.A.
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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_429704693
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.
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.
Title: Reinforcement Learning: An Introduction (...
Publisher: A Bradford Book
Publication Date: 1998
Binding: Hardcover
Condition: Good
Seller: Books From California, Simi Valley, CA, U.S.A.
hardcover. Condition: Good. Seller Inventory # mon0003921014
Seller: HPB-Red, Dallas, TX, U.S.A.
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
Seller: BooksRun, Philadelphia, PA, U.S.A.
Hardcover. Condition: Fair. First Edition. The item might be beaten up but readable. May contain markings or highlighting, as well as stains, bent corners, or any other major defect, but the text is not obscured in any way. Seller Inventory # 0262193981-7-1
Seller: BooksRun, Philadelphia, PA, U.S.A.
Hardcover. Condition: Good. First Edition. It's a preowned item in good condition and includes all the pages. It may have some general signs of wear and tear, such as markings, highlighting, slight damage to the cover, minimal wear to the binding, etc., but they will not affect the overall reading experience. Seller Inventory # 0262193981-11-1
Seller: 3Brothers Bookstore, Egg harbor township, NJ, U.S.A.
Condition: good. Books may contain some notes and highlighting. Supplements such as Access Codes, Cd's Dust Jackets, etc. are not guaranteed with used book purchases. Seller Inventory # EVV.0262193981.G
Seller: Half Price Books Inc., Dallas, TX, U.S.A.
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
Seller: ReviBlio, Barcelona, B, Spain
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
Seller: Sekkes Consultants, North Dighton, MA, U.S.A.
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
Seller: Anybook.com, Lincoln, United Kingdom
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
Quantity: 1 available
Seller: Buchpark, Trebbin, Germany
Condition: Gut. Zustand: Gut | Seiten: 344 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar. Seller Inventory # 1509267/203