Selected topics on continuous-time controlled Markov chains and Markov games.
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| 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 |
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| 100 | 1 | |a Prieto-Rumeau, Tomás. | |
| 245 | 1 | 0 | |a Selected topics on continuous-time controlled Markov chains and Markov games. |
| 260 | |a London : |b Imperial College Press ; |a Singapore ; |a Hackensack, NJ : |b Distributed by World Scientific Publishing Co., |c ©2012. | ||
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 490 | 1 | |a ICP advanced texts in mathematics ; |v v. 5 | |
| 588 | 0 | |a Online resource; title from digital title page (viewed May 24, 2012). | |
| 520 | |a 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. | ||
| 505 | 0 | |a Preface; Contents; 1. Introduction; 1.1 Preliminary examples; 1.1.1 A controlled population system; 1.1.2 A prey-predator game model; 1.2 Overview of the book; 1.3 Contents; 1.4 Notation; 2. Controlled Markov Chains; 2.1 Introduction; 2.2 The control model; 2.3 Existence of controlled Markov chains; 2.4 Exponential ergodicity; 2.5 Proof of Theorem 2.11; 2.6 Conclusions; 3. Basic Optimality Criteria; 3.1 Introduction; 3.2 The finite horizon case; 3.3 The infinite horizon discounted reward; 3.3.1 Definitions; 3.3.2 The discounted reward optimality equation; 3.3.3 The uniformization technique. | |
| 504 | |a Includes bibliographical references (pages 265-274) and index. | ||
| 650 | 0 | |a Markov processes. |0 http://id.loc.gov/authorities/subjects/sh85081369 | |
| 650 | 0 | |a Stochastic processes. |0 http://id.loc.gov/authorities/subjects/sh85128181 | |
| 650 | 7 | |a MATHEMATICS |x Probability & Statistics |x Stochastic Processes. |2 bisacsh | |
| 650 | 7 | |a Markov processes. |2 fast |0 (OCoLC)fst01010347 | |
| 650 | 7 | |a Stochastic processes. |2 fast |0 (OCoLC)fst01133519 | |
| 655 | 0 | |a Electronic books. | |
| 655 | 4 | |a Electronic books. | |
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| 830 | 0 | |a Imperial College Press advanced texts in mathematics ; |v v. 5. |0 http://id.loc.gov/authorities/names/no2007087803 | |
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