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hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
hal.structure.identifierQuality control and dynamic reliability [CQFD]
dc.contributor.authorDUFOUR, François
hal.structure.identifierDepartment of Statistics and Operations Research [Madrid]
dc.contributor.authorPRIETO-RUMEAU, Tomás
dc.date.accessioned2024-04-04T03:16:40Z
dc.date.available2024-04-04T03:16:40Z
dc.date.issued2015
dc.identifier.issn1744-2508
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/194237
dc.description.abstractEnWe consider a discrete-time Markov decision process with Borel state and action spaces, and possibly unbounded cost function. We assume that the Markov transition kernel is absolutely continuous with respect to some probability measure . By replacing this probability measure with its empirical distribution for a sample of size n, we obtain a finite state space control problem, which is used to provide an approximation of the optimal value and an optimal policy of the original control model. We impose Lipschitz continuity properties on the control model and its associated density functions. We measure the accuracy of the approximation of the optimal value and an optimal policy by means of a non-asymptotic concentration inequality based on the 1-Wasserstein distance between and . Obtaining numerically the solution of the approximating control model is discussed and an application to an inventory management problem is presented.
dc.language.isoen
dc.publisherTaylor & Francis: STM, Behavioural Science and Public Health Titles
dc.subject.enWasserstein distance
dc.subject.enConcentration inequalities
dc.subject.enApproximation of the optimal value and an optimal policy
dc.subject.enLong-run average cost
dc.subject.enMarkov decision processes
dc.title.enApproximation of average cost Markov decision processes using empirical distributions and concentration inequalities
dc.typeArticle de revue
dc.identifier.doi10.1080/17442508.2014.939979
dc.subject.halMathématiques [math]/Optimisation et contrôle [math.OC]
bordeaux.journalStochastics: An International Journal of Probability and Stochastic Processes
bordeaux.page273 - 307
bordeaux.volume87
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.issue2
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierhal-01246225
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01246225v1
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