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Linear-quadratic mean-field type stackelberg differential games for stochastic jump-diffusion systems

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dc.contributor.authorMoon, Jun-
dc.date.accessioned2022-07-19T05:05:41Z-
dc.date.available2022-07-19T05:05:41Z-
dc.date.issued2022-06-
dc.identifier.issn2156-8472-
dc.identifier.issn2156-8499-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/170172-
dc.description.abstractIn this paper, we consider linear-quadratic (LQ) leader-follower Stackelberg differential games for mean-field type stochastic systems with jump diffusions, where the system includes mean-field variables, i.e., the expected value of state and control variables. We first solve the LQ mean-field type control problem of the follower using the stochastic maximum principle and obtain the state-feedback representation of the open-loop optimal solution in terms of the coupled integro-Riccati differential equations (CIRDEs) via the Four-Step Scheme. Next, we solve the problem of the leader, which is the LQ control problem subject to the mean-field type forward-backward stochastic system with jump diffusions, where the constraint characterizes the rational behavior of the follower. Using the variational approach, we obtain the (mean-field type) stochastic maximum principle. However, to obtain the state-feedback representation of the open-loop optimal solution of the leader, there is a technical challenge due to the jump process. We consider two different cases, in which the state-feedback type control in terms of the CIRDEs can be characterized by generalizing the Four-Step Scheme. We finally show that the state-feedback type controls of the open-loop optimal solutions for the leader and the follower constitute the Stackelberg equilibrium.-
dc.format.extent34-
dc.language영어-
dc.language.isoENG-
dc.publisherAmerican Institute of Mathematical Sciences-
dc.titleLinear-quadratic mean-field type stackelberg differential games for stochastic jump-diffusion systems-
dc.typeArticle-
dc.publisher.location미국-
dc.identifier.doi10.3934/mcrf.2021026-
dc.identifier.scopusid2-s2.0-85121130236-
dc.identifier.wosid000706686200001-
dc.identifier.bibliographicCitationMathematical Control and Related Fields, v.12, no.2, pp 371 - 404-
dc.citation.titleMathematical Control and Related Fields-
dc.citation.volume12-
dc.citation.number2-
dc.citation.startPage371-
dc.citation.endPage404-
dc.type.docType정기학술지(Article(Perspective Article포함))-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaMathematics-
dc.relation.journalWebOfScienceCategoryMathematics, Applied-
dc.relation.journalWebOfScienceCategoryMathematics-
dc.subject.keywordPlusMAXIMUM PRINCIPLE-
dc.subject.keywordPlusEQUATIONS-
dc.subject.keywordPlusDELAY-
dc.subject.keywordPlusMODEL-
dc.subject.keywordAuthorMean-field stochastic systems with jump diffusions-
dc.subject.keywordAuthorStackelberg game-
dc.subject.keywordAuthormean-field type LQ control-
dc.subject.keywordAuthorintegro-Riccati differential equation-
dc.identifier.urlhttps://www.aimsciences.org/article/doi/10.3934/mcrf.2021026-
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