Decision Making Under Uncertainty and Reinforcement Learning

Name: Decision Making Under Uncertainty and Reinforcement Learning
Author: Christos Dimitrakakis

Theory and Algorithms

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Gebonden, blz. | Engels

Springer International Publishing | e druk, 2022

ISBN13: 9783031076121

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Springer International Publishing e druk, 2022 9783031076121

Onderdeel van serie Intelligent Systems Reference Library

€ 180,99

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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.

Specificaties

ISBN13:9783031076121

Taal:Engels

Bindwijze:gebonden

Uitgever:Springer International Publishing

Serie:Intelligent Systems Reference Library

Inhoudsopgave

Introduction.- Subjective probability and utility.- Decision problems.- Estimation. 

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Decision Making Under Uncertainty and Reinforcement Learning

Theory and Algorithms

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