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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Decision Making Under Uncertainty and Reinforcement Learning | Theory and Algorithms | Christos Dimitrakakis (u. a.) | Taschenbuch | Intelligent Systems Reference Library | xiii | Englisch | 2023 | Springer | EAN 9783031108921 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Condizione: New. 1st ed. 2022 edition NO-PA16APR2015-KAP.
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Editore: Springer International Publishing, Springer International Publishing, 2023
ISBN 10: 3031108922 ISBN 13: 9783031108921
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents recent research in decision making under uncertainty, in particular reinforcement learning and learning with expert advice. The core elements of decision theory, Markov decision processes and reinforcement learning have not been previously collected in a concise volume. Our aim with this book was to provide a solid theoretical foundation with elementary proofs of the most important theorems in the field, all collected in one place, and not typically found in introductory textbooks. This book is addressed to graduate students that are interested in statistical decision making under uncertainty and the foundations of reinforcement learning.
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book presents recent research in decision making under uncertainty, in particular reinforcement learning and learning with expert advice. The core elements of decision theory, Markov decision processes and reinforcement learning have not been previo.
Lingua: Inglese
Editore: Springer International Publishing, Springer International Publishing Dez 2023, 2023
ISBN 10: 3031108922 ISBN 13: 9783031108921
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents recent research in decision making under uncertainty, in particular reinforcement learning and learning with expert advice. The core elements of decision theory, Markov decision processes and reinforcement learning have not been previously collected in a concise volume. Our aim with this book was to provide a solid theoretical foundation with elementary proofs of the most important theorems in the field, all collected in one place, and not typically found in introductory textbooks. This book is addressed to graduate students that are interested in statistical decision making under uncertainty and the foundations of reinforcement learning. 260 pp. Englisch.
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Lingua: Inglese
Editore: Springer, Springer Dez 2023, 2023
ISBN 10: 3031108922 ISBN 13: 9783031108921
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Presents recent research in decision making under uncertainty, and in particular reinforcement learning and learning with expert adviceRelate the theory to practical problems in reinforcement learning, artificial intelligence and cognitive scienceGives a thorough understanding of statistical decision theory, the meaning of hypothesis testing, automatic methods for designing and interpreting experiments and the relation of statistical decision making to human decision makingSpringer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 260 pp. Englisch.
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