This item is printed on demand - Print on Demand Titel. Neuware -This book offers a systematic and rigorous treatment of continuous-time Markov decision processes, covering both theory and possible applications to queueing systems, epidemiology, finance, and other fields. Unlike most books on the subject, much attention is paid to problems with functional constraints and the realizability of strategies.Three major methods of investigations are presented, based on dynamic programming, linear programming, and reduction to discrete-time problems. Although the main focus is on models with total (discounted or undiscounted) cost criteria, models with average cost criteria and with impulsive controls are also discussed in depth.The book is self-contained. A separate chapter is devoted to Markov pure jump processes and the appendices collect the requisite background on real analysis and applied probability. All the statements in the main text are proved in detail.Researchers and graduate students in applied probability, operational research, statistics and engineering will find this monograph interesting, useful and valuable.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 608 pp. Englisch.

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Detalles bibliogr�ficos

T�tulo: Continuous-Time Markov Decision Processes
Editor: Springer International Publishing, Springer International Publishing Nov 2021
Fecha de publicaci�n: 2021
Idioma: Ingl�s
ISBN 10: 3030549895
ISBN 13: 9783030549893
Encuadernaci�n: Taschenbuch
Estado: Neu
Dimensiones: 235�mil�metros de ancho por 155 de alto por 33 de largo
Peso: 908 gramos

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Sinopsis

This book offers a systematic and rigorous treatment of continuous-time Markov decision processes, covering both theory and possible applications to queueing systems, epidemiology, finance, and other fields. Unlike most books on the subject, much attention is paid to problems with functional constraints and the realizability of strategies.

Three major methods of investigations are presented, based on dynamic programming, linear programming, and reduction to discrete-time problems. Although the main focus is on models with total (discounted or undiscounted) cost criteria, models with average cost criteria and with impulsive controls are also discussed in depth.

The book is self-contained. A separate chapter is devoted to Markov pure jump processes and the appendices collect the requisite background on real analysis and applied probability. All the statements in the main text are proved in detail.

Researchers and graduate students in applied probability, operational research, statistics and engineering will find this monograph interesting, useful and valuable.

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Alexey Piunovskiy was born in Moscow, USSR, in 1954. He obtained his PhD in 1981 from the Moscow State Institute of Electronics and Mathematics, and his DSc from the Moscow State Institute of Physics and Technology in 2000. Since then he has been at the University of Liverpool, where he is presently a Reader. His research interests include stochastic optimal control and constrained optimization.

Yi Zhang was born in Qingdao, PRC, in 1985. He obtained his PhD in 2010 from the Department of Mathematical Sciences at the University of Liverpool, where he is currently a Lecturer. His research interests include stochastic models in operational research, Markov decision processes and their applications to problems in statistics and optimal control.

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