Selected topics on continuous-time controlled Markov chains and Markov games.:
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...
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
London : Singapore ; Hackensack, NJ :
Imperial College Press ; Distributed by World Scientific Publishing Co.,
©2012.
|
| Schriftenreihe: | Imperial College Press advanced texts in mathematics ;
v. 5. |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | 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. |
| Beschreibung: | 1 online resource (1 online resource) |
| Bibliographie: | Includes bibliographical references (pages 265-274) and index. |
| ISBN: | 9781848168497 1848168497 1848168489 9781848168480 |
Internformat
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| 245 | 1 | 0 | |a Selected topics on continuous-time controlled Markov chains and Markov games. |
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| 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. | ||
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| 650 | 2 | |a Stochastic Processes |0 https://id.nlm.nih.gov/mesh/D013269 | |
| 650 | 6 | |a Processus de Markov. | |
| 650 | 6 | |a Processus stochastiques. | |
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| author | Prieto-Rumeau, Tomás |
| author_facet | Prieto-Rumeau, Tomás |
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| contents | 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. |
| ctrlnum | (OCoLC)794306954 |
| dewey-full | 519.233 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.233 |
| dewey-search | 519.233 |
| dewey-sort | 3519.233 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| format | Electronic eBook |
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| id | ZDB-4-EBA-ocn794306954 |
| illustrated | Not Illustrated |
| indexdate | 2024-10-25T16:18:39Z |
| institution | BVB |
| isbn | 9781848168497 1848168497 1848168489 9781848168480 |
| language | English |
| oclc_num | 794306954 |
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| publisher | Imperial College Press ; Distributed by World Scientific Publishing Co., |
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| series | Imperial College Press advanced texts in mathematics ; |
| series2 | ICP advanced texts in mathematics ; |
| spelling | Prieto-Rumeau, Tomás. Selected topics on continuous-time controlled Markov chains and Markov games. London : Imperial College Press ; Singapore ; Hackensack, NJ : Distributed by World Scientific Publishing Co., ©2012. 1 online resource (1 online resource) text txt rdacontent computer c rdamedia online resource cr rdacarrier ICP advanced texts in mathematics ; v. 5 Online resource; title from digital title page (viewed May 24, 2012). 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. 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. Includes bibliographical references (pages 265-274) and index. Markov processes. http://id.loc.gov/authorities/subjects/sh85081369 Stochastic processes. http://id.loc.gov/authorities/subjects/sh85128181 Markov Chains https://id.nlm.nih.gov/mesh/D008390 Stochastic Processes https://id.nlm.nih.gov/mesh/D013269 Processus de Markov. Processus stochastiques. MATHEMATICS Probability & Statistics Stochastic Processes. bisacsh Markov processes fast Stochastic processes fast 1848168489 9781848168480 Imperial College Press advanced texts in mathematics ; v. 5. http://id.loc.gov/authorities/names/no2007087803 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=457217 Volltext CBO01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=457217 Volltext |
| spellingShingle | Prieto-Rumeau, Tomás Selected topics on continuous-time controlled Markov chains and Markov games. Imperial College Press advanced texts in mathematics ; 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. Markov processes. http://id.loc.gov/authorities/subjects/sh85081369 Stochastic processes. http://id.loc.gov/authorities/subjects/sh85128181 Markov Chains https://id.nlm.nih.gov/mesh/D008390 Stochastic Processes https://id.nlm.nih.gov/mesh/D013269 Processus de Markov. Processus stochastiques. MATHEMATICS Probability & Statistics Stochastic Processes. bisacsh Markov processes fast Stochastic processes fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85081369 http://id.loc.gov/authorities/subjects/sh85128181 https://id.nlm.nih.gov/mesh/D008390 https://id.nlm.nih.gov/mesh/D013269 |
| title | Selected topics on continuous-time controlled Markov chains and Markov games. |
| title_auth | Selected topics on continuous-time controlled Markov chains and Markov games. |
| title_exact_search | Selected topics on continuous-time controlled Markov chains and Markov games. |
| title_full | Selected topics on continuous-time controlled Markov chains and Markov games. |
| title_fullStr | Selected topics on continuous-time controlled Markov chains and Markov games. |
| title_full_unstemmed | Selected topics on continuous-time controlled Markov chains and Markov games. |
| title_short | Selected topics on continuous-time controlled Markov chains and Markov games. |
| title_sort | selected topics on continuous time controlled markov chains and markov games |
| topic | Markov processes. http://id.loc.gov/authorities/subjects/sh85081369 Stochastic processes. http://id.loc.gov/authorities/subjects/sh85128181 Markov Chains https://id.nlm.nih.gov/mesh/D008390 Stochastic Processes https://id.nlm.nih.gov/mesh/D013269 Processus de Markov. Processus stochastiques. MATHEMATICS Probability & Statistics Stochastic Processes. bisacsh Markov processes fast Stochastic processes fast |
| topic_facet | Markov processes. Stochastic processes. Markov Chains Stochastic Processes Processus de Markov. Processus stochastiques. MATHEMATICS Probability & Statistics Stochastic Processes. Markov processes Stochastic processes |
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