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dc.contributor.authorNutz, Marcel
dc.contributor.authorBouchard, Bruno
dc.date.accessioned2011-05-30T09:37:40Z
dc.date.available2011-05-30T09:37:40Z
dc.date.issued2012
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/6352
dc.language.isoenen
dc.subjectComparison theoremen
dc.subjectViscosity solutionen
dc.subjectHamilton-Jacobi-Bellman equationen
dc.subjectExpectation constrainten
dc.subjectState constrainten
dc.subjectWeak dynamic programmingen
dc.subject.ddc519en
dc.titleWeak Dynamic Programming for Generalized State Constraintsen
dc.typeArticle accepté pour publication ou publié
dc.contributor.editoruniversityotherDepartment of Mathematics Swiss Federal Institute of Technology in Zurich;Suisse
dc.contributor.editoruniversityotherCentre de Recherche en Économie et Statistique (CREST);France
dc.description.abstractenWe provide a dynamic programming principle for stochastic optimal control problems with expectation constraints. A weak formulation, using test functions and a probabilistic relaxation of the constraint, avoids restrictions related to a measurable selection but still implies the Hamilton-Jacobi-Bellman equation in the viscosity sense. We treat open state constraints as a special case of expectation constraints and prove a comparison theorem to obtain the equation for closed state constraints.en
dc.relation.isversionofjnlnameSIAM Journal on Control and Optimization
dc.relation.isversionofjnlvol50
dc.relation.isversionofjnlissue6
dc.relation.isversionofjnldate2012
dc.relation.isversionofjnlpages3344-3373
dc.relation.isversionofdoihttp://dx.doi.org/10.1137/110852942
dc.description.sponsorshipprivateouien
dc.relation.isversionofjnlpublisherSIAM
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
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