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Springer Decision Making Under Uncertainty and Reinforcement Learning: Theory and Algorithms: 223 (Intelligent Systems Reference Library, 223)

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Description

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

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
07 December 2023
Listed Since
08 June 2022

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