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dc.contributor.authorBouchard, Bruno
dc.contributor.authorDang, Ngoc Minh
dc.date.accessioned2011-01-17T10:36:28Z
dc.date.available2011-01-17T10:36:28Z
dc.date.issued2012
dc.identifier.issn0167-6911
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/5482
dc.language.isoenen
dc.subjectStochastic target
dc.subjectstochastic control
dc.subjectviscosity solutions
dc.subject.ddc519en
dc.titleOptimal Control versus Stochastic Target problems: An Equivalence Result
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenWithin a general abstract framework, we show that any optimal control problem instandard form can be translated into a stochastic target problem as de ned in [17], whenever the underlying ltered probability space admits a suitable martingale representationproperty. This provides a uni ed way of treating these two classes of stochastic con-trol problems. As an illustration, we show, within a jump di usion framework, how theHamilton-Jacobi-Bellman equations associated to an optimal control problem in standard form can be easily retrieved from the partial di erential equations associated to itsstochastic target counterpart.
dc.relation.isversionofjnlnameSystems & Control Letters
dc.relation.isversionofjnlvol61
dc.relation.isversionofjnlissue2
dc.relation.isversionofjnldate2012
dc.relation.isversionofjnlpages343-346
dc.relation.isversionofdoihttp://dx.doi.org/10.1016/j.sysconle.2011.11.010
dc.description.sponsorshipprivateouien
dc.relation.isversionofjnlpublisherElsevier
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
dc.description.ssrncandidatenon
dc.description.halcandidateoui
dc.description.readershiprecherche
dc.description.audienceInternational
dc.relation.Isversionofjnlpeerreviewedoui
dc.date.updated2017-01-18T15:19:06Z


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