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dc.contributor.authorLichun Li
dc.contributor.authorLangbort, Cedric
dc.contributor.authorShamma, Jeff S.
dc.date.accessioned2017-10-03T12:49:33Z
dc.date.available2017-10-03T12:49:33Z
dc.date.issued2017-07-10
dc.identifier.citationLichun Li, Langbort C, Shamma J (2017) Computing security strategies in finite horizon repeated Bayesian games. 2017 American Control Conference (ACC). Available: http://dx.doi.org/10.23919/ACC.2017.7963514.
dc.identifier.doi10.23919/ACC.2017.7963514
dc.identifier.urihttp://hdl.handle.net/10754/625673
dc.description.abstractThis paper studies security strategies in two-player zero-sum repeated Bayesian games with finite horizon. In such games, each player has a private type which is independently chosen according to a publicly known a priori probability. Players' types are fixed all through the game. The game is played for finite stages. At every stage, players simultaneously choose their actions which are observed by the public. The one-stage payoff of player 1 (or penalty to player 2) depends on both players types and actions, and is not directly observed by any player. While player 1 aims to maximize the total payoff over the game, player 2 wants to minimize it. This paper provides each player two ways to compute the security strategy, i.e. the optimal strategy in the worst case. First, a security strategy that directly depends on both players' history actions is derived by refining the sequence form. Noticing that history action space grows exponentially with respect to the time horizon, this paper further presents a security strategy that depends on player's fixed sized sufficient statistics. The sufficient statistics is shown to consist of the belief on one's own type, the regret on the other player's type, and the stage, and is independent of the other player's strategy.
dc.description.sponsorshipThe authors acknowledge the financial support of ARO project #W911NF-09-1-0553 and the AFOSR/MURI project #FA9550-10-1-0573.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttp://ieeexplore.ieee.org/document/7963514/
dc.subjectBayes methods
dc.subjectComputer security
dc.subjectGames
dc.subjectHistory
dc.subjectNash equilibrium
dc.titleComputing security strategies in finite horizon repeated Bayesian games
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentElectrical Engineering Program
dc.identifier.journal2017 American Control Conference (ACC)
dc.conference.date2017-05-24 to 2017-05-26
dc.conference.name2017 American Control Conference, ACC 2017
dc.conference.locationSeattle, WA, USA
dc.contributor.institutionCoordinated Science Lab at UIUC, United States of America
kaust.personShamma, Jeff S.
dc.date.published-online2017-07-10
dc.date.published-print2017-05


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