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Continuous-time Markov decision proc...

Piunovskiy, Alexey.

Continuous-time Markov decision processesBorel space models and general control strategies /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Continuous-time Markov decision processesby Alexey Piunovskiy, Yi Zhang.
Reminder of title:	Borel space models and general control strategies /
Author:	Piunovskiy, Alexey.
other author:	Zhang, Yi.
Published:	Cham :Springer International Publishing :2020.
Description:	xxiv, 583 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Markov processes.
Online resource:	https://doi.org/10.1007/978-3-030-54987-9
ISBN:	9783030549879$q(electronic bk.)

Continuous-time Markov decision processesBorel space models and general control strategies /
Piunovskiy, Alexey.

Continuous-time Markov decision processesBorel space models and general control strategies /[electronic resource] :by Alexey Piunovskiy, Yi Zhang. - Cham :Springer International Publishing :2020. - xxiv, 583 p. :ill. (some col.), digital ;24 cm. - Probability theory and stochastic modelling,v.972199-3130 ;. - Probability theory and stochastic modelling ;v.70..

Foreword -- Preface -- Description of CTMDPs and Preliminaries -- Selected Properties of Controlled Processes -- The Discounted Cost Model -- Reduction to DTMDP: The Total Cost Model -- The Average Cost Model -- The Total Cost Model: General Case -- Gradual-Impulsive Control Models -- Appendices: Miscellaneous Results -- Relevant Definitions and Facts -- Definitions and Facts about Discrete-Time Markov Decision Processes -- Bibliography -- Index -- Notation.

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.

ISBN: 9783030549879$q(electronic bk.)

Standard No.: 10.1007/978-3-030-54987-9doiSubjects--Topical Terms:

181910
Markov processes.

LC Class. No.: QA274.7 / .P586 2020

Dewey Class. No.: 519.233

Continuous-time Markov decision processesBorel space models and general control strategies /
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245 1 0 $a Continuous-time Markov decision processes $h [electronic resource] : $b Borel space models and general control strategies / $c by Alexey Piunovskiy, Yi Zhang.
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505 0 $a Foreword -- Preface -- Description of CTMDPs and Preliminaries -- Selected Properties of Controlled Processes -- The Discounted Cost Model -- Reduction to DTMDP: The Total Cost Model -- The Average Cost Model -- The Total Cost Model: General Case -- Gradual-Impulsive Control Models -- Appendices: Miscellaneous Results -- Relevant Definitions and Facts -- Definitions and Facts about Discrete-Time Markov Decision Processes -- Bibliography -- Index -- Notation.
520 $a 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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