Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/93870
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dc.contributorDepartment of Applied Mathematicsen_US
dc.creatorHuang, Jen_US
dc.creatorWang, BCen_US
dc.creatorXie, Ten_US
dc.date.accessioned2022-08-03T01:24:01Z-
dc.date.available2022-08-03T01:24:01Z-
dc.identifier.issn1292-8119en_US
dc.identifier.urihttp://hdl.handle.net/10397/93870-
dc.language.isoenen_US
dc.publisherEDP Sciencesen_US
dc.rights© EDP Sciences, SMAI 2021en_US
dc.rightsThe original publication is available at https://www.esaim-cocv.org/.en_US
dc.rightsThe following publication Huang, J., Wang, B. C., & Xie, T. (2021). Social optima in leader-follower mean field linear quadratic control. ESAIM: Control, Optimisation and Calculus of Variations, 27, S12 is available at https://doi.org/10.1051/cocv/2020056en_US
dc.subjectForward-backward stochastic differential equationen_US
dc.subjectLeader-follower problemen_US
dc.subjectLinear quadratic controlen_US
dc.subjectSocial optimalityen_US
dc.subjectWeakly-coupled stochastic systemen_US
dc.titleSocial optima in leader-follower mean field linear quadratic controlen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume27en_US
dc.identifier.doi10.1051/cocv/2020056en_US
dcterms.abstractThis paper investigates a linear quadratic mean field leader-follower team problem, where the model involves one leader and a large number of weakly-coupled interactive followers. The leader and the followers cooperate to optimize the social cost. Specifically, for any strategy provided first by the leader, the followers would like to choose a strategy to minimize social cost functional. Using variational analysis and person-by-person optimality, we construct two auxiliary control problems. By solving sequentially, the auxiliary control problems with consistent mean field approximations, we can obtain a set of decentralized social optimality strategy with help of a class of forward-backward consistency systems. The relevant Stackelberg equilibrium is further proved under some proper conditions.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationESAIM. Control, optimisation and calculus of variations, 2021, v. 27, S12en_US
dcterms.isPartOfESAIM. Control, optimisation and calculus of variationsen_US
dcterms.issued2021-
dc.identifier.scopus2-s2.0-85101987560-
dc.identifier.eissn1262-3377en_US
dc.identifier.artnS12en_US
dc.description.validate202208 bcfcen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberAMA-0067-
dc.description.fundingSourceRGCen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS54171306-
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