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.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Andrew G. Barto is Professor of Computer Science at the University of Massachusetts.
Richard S. Sutton is Senior Research Scientist, Department of Computer Science, University of Massachusetts.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Da: Better World Books, Mishawaka, IN, U.S.A.
Condizione: Very Good. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good. Codice articolo 9002566-6
Quantità: 1 disponibili
Da: HPB-Red, Dallas, TX, U.S.A.
Hardcover. Condizione: 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! Codice articolo S_469105041
Quantità: 1 disponibili
Da: HPB-Red, Dallas, TX, U.S.A.
Hardcover. Condizione: Acceptable. Connecting readers with great books since 1972. Used textbooks may not include companion materials such as access codes, etc. May have condition issues including wear and notes/highlighting. We ship orders daily and Customer Service is our top priority! Codice articolo S_487069468
Quantità: 1 disponibili
Da: WorldofBooks, Goring-By-Sea, WS, Regno Unito
Paperback. Condizione: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged. Codice articolo GOR005124400
Quantità: 1 disponibili
Da: Book Gurus, Tallahassee, FL, U.S.A.
hardcover. Condizione: Fine. Codice articolo 01KX3R98ZAXRS3Q
Quantità: 1 disponibili
Da: Sekkes Consultants, North Dighton, MA, U.S.A.
Hardcover. Condizione: Near fine. Condizione sovraccoperta: 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. Codice articolo 278286
Quantità: 1 disponibili
Da: Anybook.com, Lincoln, Regno Unito
Condizione: 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. Codice articolo 4315703
Quantità: 1 disponibili
Da: GoldBooks, Denver, CO, U.S.A.
Hardcover. Condizione: new. New Copy. Customer Service Guaranteed. Codice articolo 12W50_51_0262193981
Quantità: 1 disponibili
Da: Duru Media, Tallahassee, FL, U.S.A.
hardcover. Condizione: New. Codice articolo 01KRDV8P4QFKXDJ
Quantità: 1 disponibili
Da: DeckleEdge LLC, Albuquerque, NM, U.S.A.
hardcover. Condizione: new. Codice articolo Shelfdream0262193981
Quantità: 1 disponibili