| Description |
1 online resource |
| Series |
Stochastic Modelling and Applied Probability ; 62 |
|
Stochastic modelling and applied probability ; 62.
|
| Contents |
And Summary -- Continuous-Time Markov Decision Processes -- Average Optimality for Finite Models -- Discount Optimality for Nonnegative Costs -- Average Optimality for Nonnegative Costs -- Discount Optimality for Unbounded Rewards -- Average Optimality for Unbounded Rewards -- Average Optimality for Pathwise Rewards -- Advanced Optimality Criteria -- Variance Minimization -- Constrained Optimality for Discount Criteria -- Constrained Optimality for Average Criteria |
| Summary |
Continuous-time Markov decision processes (MDPs), also known as controlled Markov chains, are used for modeling decision-making problems that arise in operations research (for instance, inventory, manufacturing, and queueing systems), computer science, communications engineering, control of populations (such as fisheries and epidemics), and management science, among many other fields. This volume provides a unified, systematic, self-contained presentation of recent developments on the theory and applications of continuous-time MDPs. The MDPs in this volume include most of the cases that arise in applications, because they allow unbounded transition and reward/cost rates. Much of the material appears for the first time in book form |
| Bibliography |
Includes bibliographical references and index |
| Notes |
English |
|
Print version record |
| Subject |
Markov processes.
|
|
Distribution (Probability theory)
|
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Markov Chains
|
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distribution (statistics-related concept)
|
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MATHEMATICS -- Probability & Statistics -- Stochastic Processes.
|
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Markov processes.
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Markov processes
|
| Form |
Electronic book
|
| Author |
Hernández-Lerma, O. (Onésimo)
|
| ISBN |
9783642025471 |
|
3642025471 |
|
3642025463 |
|
9783642025464 |
|
1282363050 |
|
9781282363052 |
|
9786612363054 |
|
6612363053 |
|
