Selected topics on continuous-time controlled Markov chains and Markov games.

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Bibliographic Details
Author / Creator:Prieto-Rumeau, Tomás.
Imprint:London : Imperial College Press ; Singapore ; Hackensack, NJ : Distributed by World Scientific Publishing Co., ©2012.
Description:1 online resource
Language:English
Series:ICP advanced texts in mathematics ; v. 5
Imperial College Press advanced texts in mathematics ; v. 5.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11132962
Hidden Bibliographic Details
ISBN:9781848168497
1848168497
1848168489
9781848168480
Notes:Includes bibliographical references (pages 265-274) and index.
Online resource; title from digital title page (viewed May 24, 2012).
Summary:This book concerns continuous-time controlled Markov chains, also known as continuous-time Markov decision processes. They form a class of stochastic control problems in which a single decision-maker wishes to optimize a given objective function. This book is also concerned with Markov games, where two decision-makers (or players) try to optimize their own objective function. Both decision-making processes appear in a large number of applications in economics, operations research, engineering, and computer science, among other areas. An extensive, self-contained, up-to-date analysis of basic o.
Other form:1848168489
9781848168480
Description
Summary:This book concerns continuous-time controlled Markov chains, also known as continuous-time Markov decision processes. They form a class of stochastic control problems in which a single decision-maker wishes to optimize a given objective function. This book is also concerned with Markov games, where two decision-makers (or players) try to optimize their own objective function. Both decision-making processes appear in a large number of applications in economics, operations research, engineering, and computer science, among other areas.An extensive, self-contained, up-to-date analysis of basic optimality criteria (such as discounted and average reward), and advanced optimality criteria (e.g., bias, overtaking, sensitive discount, and Blackwell optimality) is presented. A particular emphasis is made on the application of the results herein: algorithmic and computational issues are discussed, and applications to population models and epidemic processes are shown.This book is addressed to students and researchers in the fields of stochastic control and stochastic games. Moreover, it could be of interest also to undergraduate and beginning graduate students because the reader is not supposed to have a high mathematical background: a working knowledge of calculus, linear algebra, probability, and continuous-time Markov chains should suffice to understand the contents of the book.
Physical Description:1 online resource
Bibliography:Includes bibliographical references (pages 265-274) and index.
ISBN:9781848168497
1848168497
1848168489
9781848168480