High order variational numerical schemes with application to Nash -MFG vaccination games
hal.structure.identifier | CEntre de REcherches en MAthématiques de la DEcision [CEREMADE] | |
dc.contributor.author | Laguzet, Laetitia
HAL ID: 10765 | * |
dc.date.accessioned | 2018-01-12T13:36:47Z | |
dc.date.available | 2018-01-12T13:36:47Z | |
dc.date.issued | 2018 | |
dc.identifier.issn | 0035-5038 | |
dc.identifier.uri | https://basepub.dauphine.fr/handle/123456789/17303 | |
dc.language.iso | en | en |
dc.subject | Variational scheme | |
dc.subject | Mean Field Games | |
dc.subject | Nash equilibrium | |
dc.subject | Vaccination games | |
dc.subject | SIR model | |
dc.subject.ddc | 515 | en |
dc.title | High order variational numerical schemes with application to Nash -MFG vaccination games | |
dc.type | Article accepté pour publication ou publié | |
dc.description.abstracten | This paper introduces high-order explicit Runge-Kutta numerical schemes in metric spaces. We show that our approach reduces to corresponding Runge-Kutta schemes if the ambient space is Hilbert. We apply these schemes to compute the Nash equilibrium in a Mean Field vaccination Game. Numerical simulations show improvement in the speed of convergence towards the Nash equilibrium; the numerical scheme has high order (two to four) in time. | |
dc.relation.isversionofjnlname | Ricerche di Matematica | |
dc.relation.isversionofjnlvol | 67 | |
dc.relation.isversionofjnlissue | 1 | |
dc.relation.isversionofjnldate | 2018 | |
dc.relation.isversionofjnlpages | 247-269 | |
dc.relation.isversionofdoi | 10.1007/s11587-018-0366-z | |
dc.identifier.urlsite | https://hal.archives-ouvertes.fr/hal-01404619 | |
dc.relation.isversionofjnlpublisher | Springer | |
dc.subject.ddclabel | Analyse | en |
dc.description.ssrncandidate | non | |
dc.description.halcandidate | non | |
dc.description.readership | recherche | |
dc.description.audience | International | |
dc.relation.Isversionofjnlpeerreviewed | oui | |
dc.date.updated | 2018-07-20T14:29:01Z | |
hal.author.function | aut |
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