Continuous-Time Markov Decision Processes
Springer International Publishing (Verlag)
978-3-030-54986-2 (ISBN)
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.
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.
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 is a complete treatise on continuous-time Markov decision processes (CTMDPs) on Borel spaces ... . The theory presented is developed in a careful and detailed form. Moreover, several examples and applications are given. Therefore, the book is interesting from both the theoretical and applied points of view. ... It is important to mention that at the end of each chapter, bibliographical remarks are supplied which complement and clarify the information given in it." (Raúl Montes-de-Oca, Mathematical Reviews, April, 2022)
“This book is a complete treatise on continuous-time Markov decision processes (CTMDPs) on Borel spaces … . The theory presented is developed in a careful and detailed form. Moreover, several examples and applications are given. Therefore, the book is interesting from both the theoretical and applied points of view. … It is important to mention that at the end of each chapter, bibliographical remarks are supplied which complement and clarify the information given in it.” (Raúl Montes-de-Oca, Mathematical Reviews, April, 2022)
| Erscheinungsdatum | 11.11.2020 |
|---|---|
| Reihe/Serie | Probability Theory and Stochastic Modelling |
| Vorwort | Albert Nikolaevich Shiryaev |
| Zusatzinfo | XXIV, 583 p. 10 illus., 3 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 1069 g |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik |
| Schlagworte | 90C40, 60J75 • constrained optimality • continuous-time Markov decision processes • convex analytic approach • Dynamic Programming • Linear Programming • Markov pure jump processes • occupation measure • sequential analysis • statistical decision theory • Stochastic Optimal Control |
| ISBN-10 | 3-030-54986-0 / 3030549860 |
| ISBN-13 | 978-3-030-54986-2 / 9783030549862 |
| Zustand | Neuware |
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