Continuous-time Markov decision processes : theory and applications
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 populati...
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| Autors principals: | , , |
|---|---|
| Format: | Livre numérique |
| Idioma: | Anglais |
| Publicat: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Edició: | 1st ed. 2009. |
| Col·lecció: | Stochastic Modelling and Applied Probability
62 |
| Matèries: | |
| Accés en línia: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Description d'après consultation du 30 mars 2012 Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Continuous-time Markov decision processes, theory and applications, Xianping Guo, Onésimo Hernández-Lerma, 2009, Heidelberg, Springer, 1 vol. (XVII-231 p.), Stochastic Modelling and Applied Probability, 978-3-642-02546-4 • Continuous-Time Markov Decision Processes, Texte imprimé, 9783642025488 • Continuous-Time Markov Decision Processes, Texte imprimé, 9783642260728 |
Taula de continguts:
- 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