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dc.contributor.authorParise, Francesca
dc.contributor.authorOzdaglar, Asuman E
dc.date.accessioned2019-07-09T13:52:12Z
dc.date.available2019-07-09T13:52:12Z
dc.date.issued2017-12
dc.identifier.isbn9781509028733
dc.identifier.urihttps://hdl.handle.net/1721.1/121530
dc.description.abstractWe investigate the sensitivity of the Nash equilibrium of constrained network aggregative games to changes in exogenous parameters affecting the cost function of the players. This setting is motivated by two applications. The first is the analysis of interventions by a social planner with a networked objective function while the second is network routing games with atomic players and information constraints. By exploiting a primal reformulation of a sensitivity analysis result for variational inequalities, we provide a characterization of the sensitivity of the Nash equilibrium that depends on primal variables only. To derive this result we assume strong monotonicity of the mapping associated with the game. As the second main result, we derive sufficient conditions that guarantee this strong monotonicity property in network aggregative games. These two characterizations allows us to systematically study changes in the Nash equilibrium due to perturbations or parameter variations in the two applications mentioned above.en_US
dc.description.sponsorshipUnited States. Army Research Office. Multidisciplinary University Research Initiative (W911NF-12-1-0509)en_US
dc.description.sponsorshipSwiss National Foundation for the Promotion of Scientific Research (grant number P2EZP2 168812)en_US
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionof10.1109/CDC.2017.8264128en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcearXiven_US
dc.titleSensitivity analysis for network aggregative gamesen_US
dc.typeArticleen_US
dc.identifier.citationParise, Francesca and Asuman Ozdaglar. "Sensitivity analysis for network aggregative games." 2017 IEEE 56th Annual Conference on Decision and Control, 12-15 Dec. 2017.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Laboratory for Information and Decision Systemsen_US
dc.relation.journal2017 IEEE 56th Annual Conference on Decision and Controlen_US
dc.eprint.versionOriginal manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2019-06-28T16:08:38Z
dspace.date.submission2019-06-28T16:08:39Z


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