Produktbild: Decision Making Under Uncertainty and Reinforcement Learning

Decision Making Under Uncertainty and Reinforcement Learning

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171,19 €

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Theory and Algorithms, Intelligent Systems Reference Library 223

ISBN: 3031076125
ISBN 13: 9783031076121
Autor: Dimitrakakis, Christos/Ortner, Ronald
Verlag: Springer Verlag GmbH
Umfang: xiii, 243 S., 5 s/w Illustr., 62 farbige Illustr., 243 p. 67 illus., 62 illus. in color.
Erscheinungsdatum: 03.12.2022
Auflage: 1/2023
Produktform: Gebunden/Hardback
Einband: Gebunden

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.

Artikelnummer: 5609790 Kategorie:

Beschreibung

Presents recent research in decision making under uncertainty, and in particular reinforcement learning and learning with expert advice Relate the theory to practical problems in reinforcement learning, artificial intelligence and cognitive science Gives 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 making

Herstellerkennzeichnung:


Springer Verlag GmbH
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69121 Heidelberg
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E-Mail: juergen.hartmann@springer.com

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