Overview
- Features a detailed treatment of constrained problems
- Covers exponential semi-Markov decision processes
- Includes various unpublished results and illustrates the theory with new solved examples
- Introduces new and broad classes of strategies
Part of the book series: Probability Theory and Stochastic Modelling (PTSM, volume 97)
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Table of contents (7 chapters)
Keywords
About this book
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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Authors and Affiliations
About the authors
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.
Bibliographic Information
Book Title: Continuous-Time Markov Decision Processes
Book Subtitle: Borel Space Models and General Control Strategies
Authors: Alexey Piunovskiy, Yi Zhang
Series Title: Probability Theory and Stochastic Modelling
DOI: https://doi.org/10.1007/978-3-030-54987-9
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-54986-2Published: 10 November 2020
Softcover ISBN: 978-3-030-54989-3Published: 11 November 2021
eBook ISBN: 978-3-030-54987-9Published: 09 November 2020
Series ISSN: 2199-3130
Series E-ISSN: 2199-3149
Edition Number: 1
Number of Pages: XXIV, 583
Number of Illustrations: 7 b/w illustrations, 3 illustrations in colour
Topics: Probability Theory and Stochastic Processes, Statistics and Computing/Statistics Programs, Systems Theory, Control, Optimization