sutton richard s (33 Ergebnisse)

Zustand: 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.

Paperback. Zustand: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

No Binding. Zustand: Very Good. A splendid lithographic printing of an engraved portrait. This actual portrait printed in 1908. Mounted and ready to frame. This is an excellent opportunity to purchase a portrait of this eminent sportsman.

Zustand: 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.

Zustand: Very Good. First edition hard back binding in publisher's original black paper covered boards, blocked and lettered gilt back. 8vo. 9½'' x 6¼''. Contains 198 pp with archive monochrome photographs throughout. Donation copy directly from the publisher to Kent Arts Archive Library, Canterbury, Kent. This has been stored in the trust's archive and has not been circulated as a lending book with front free end paper missing, small stamp to the copyright page. Very Good condition book in Fine condition dust wrapper, not price clipped, £19.99. Member of the P.B.F.A. ROYAL NAVY (RN).

Zustand: Very Good. First edition hard back binding in publisher's original black paper covered boards, blocked and lettered gilt back. 8vo. 9½'' x 6¼''. Contains 198 pp with archive monochrome photographs throughout. Donation copy directly from the publisher to Kent Arts Archive Library, Canterbury, Kent. This has been stored in the trust's archive and has not been circulated as a lending book with front free end paper missing, small stamp to the copyright page. Very Good condition book in Fine condition dust wrapper, not price clipped, £19.99. Member of the P.B.F.A. ROYAL NAVY (RN).

No Binding. Zustand: Very Good. A photographic image printed by a lithographic process in 1881, with biographical notes. Mounted/matted and ready to frame. Attractive, decorative and unusual.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Zustand: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.

Gebunden. Zustand: New. KlappentextThis work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original w.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Zustand: New.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Hardcover. Zustand: Brand New. 2nd edition. 526 pages. 9.25x7.25x1.50 inches. In Stock.

Zustand: New. In.

Zustand: NEW.

Gebundene Ausgabe. Zustand: Gut. 180 Seiten ex Library Book aus einer wissenschaftlichen Bibliothek Sprache: Englisch Gewicht in Gramm: 469.

Zustand: New. 2018. second edition. Hardcover. . . . . . Books ship from the US and Ireland.

Zustand: New. 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.

Buch. Zustand: Neu. Neuware -The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence.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 while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics.Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.Libri GmbH, Europaallee 1, 36244 Bad Hersfeld Englisch.

Buch. Zustand: Neu. Reinforcement Learning | An Introduction | Richard S. Sutton (u. a.) | Buch | Adaptive Computation and Machine Learning series | Einband - fest (Hardcover) | Englisch | 2018 | The MIT Press | EAN 9780262039246 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.

Zustand: Gut. Zustand: Gut | Seiten: 344 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

hardcover. Zustand: Sehr gut. Auflage: second edition. 344 Seiten leichte Druckstelle am Cover u. Etikettenrest am Schutzumschlag, kleine Lagerspuren am Buch, Inhalt einwandfrei und ungelesen Sprache: Englisch Gewicht in Gramm: 860.

Buch. Zustand: Neu. Neuware - The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence.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 while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics.Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.

Zustand: New. In.

Buch. Zustand: Neu. Neuware -The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence.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 while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics.Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning. Englisch.

Taschenbuch. Zustand: Neu. Reinforcement Learning | Richard S. Sutton | Taschenbuch | 172 S. | Englisch | 2012 | Springer | EAN 9781461366089 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Reinforcement learning is the learning of a mapping from situations to actions so as to maximize a scalar reward or reinforcement signal. The learner is not told which action to take, as in most forms of machine learning, but instead must discover which actions yield the highest reward by trying them. In the most interesting and challenging cases, actions may affect not only the immediate reward, but also the next situation, and through that all subsequent rewards. These two characteristics -- trial-and-error search and delayed reward -- are the most important distinguishing features of reinforcement learning. Reinforcement learning is both a new and a very old topic in AI. The term appears to have been coined by Minsk (1961), and independently in control theory by Walz and Fu (1965). The earliest machine learning research now viewed as directly relevant was Samuel's (1959) checker player, which used temporal-difference learning to manage delayed reward much as it is used today. Of course learning and reinforcement have been studied in psychology for almost a century, and that work has had a very strong impact on the AI/engineering work. One could in fact consider all of reinforcement learning to be simply the reverse engineering of certain psychological learning processes (e.g. operant conditioning and secondary reinforcement). Reinforcement Learning is an edited volume of original research, comprising seven invited contributions by leading researchers.