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dc.contributor.authorMarden, Jason R.
dc.contributor.authorShamma, Jeff S.
dc.date.accessioned2021-04-12T06:11:12Z
dc.date.available2021-04-12T06:11:12Z
dc.date.issued2018-05-28
dc.identifier.citationMarden, J. R., & Shamma, J. S. (2018). Game Theory and Control. Annual Review of Control, Robotics, and Autonomous Systems, 1(1), 105–134. doi:10.1146/annurev-control-060117-105102
dc.identifier.issn2573-5144
dc.identifier.doi10.1146/annurev-control-060117-105102
dc.identifier.urihttp://hdl.handle.net/10754/668662
dc.description.abstractGame theory is the study of decision problems in which there are multiple decision makers and the quality of a decision maker's choice depends on both that choice and the choices of others. While game theory has been studied predominantly as a modeling paradigm in the mathematical social sciences, there is a strong connection to control systems in that a controller can be viewed as a decision-making entity. Accordingly, game theory is relevant in settings with multiple interacting controllers. This article presents an introduction to game theory, followed by a sampling of results in three specific control theory topics where game theory has played a significant role: ( a) zero-sum games, in which the two competing players are a controller and an adversarial environment; ( b) team games, in which several controllers pursue a common goal but have access to different information; and ( c) distributed control, in which both a game and online adaptive rules are designed to enable distributed interacting subsystems to achieve a collective objective.
dc.description.sponsorshipThis work was supported by Office of Naval Research grant N00014-15-1-2762, National Science Foundation grant ECCS-1351866, and funding from King Abdullah University of Science and Technology (KAUST).
dc.publisherAnnual Reviews
dc.relation.urlhttps://www.annualreviews.org/doi/10.1146/annurev-control-060117-105102
dc.rightsArchived with thanks to Annual Review of Control, Robotics, and Autonomous Systems
dc.titleGame Theory and Control
dc.typeArticle
dc.contributor.departmentComputer, Electrical and Mathematical Science and Engineering (CEMSE) Division
dc.contributor.departmentElectrical and Computer Engineering Program
dc.contributor.departmentRISC Laboratory
dc.identifier.journalAnnual Review of Control, Robotics, and Autonomous Systems
dc.eprint.versionPost-print
dc.contributor.institutionDepartment of Electrical and Computer Engineering, University of California, Santa Barbara, California 93106, USA;
dc.identifier.volume1
dc.identifier.issue1
dc.identifier.pages105-134
kaust.personShamma, Jeff S.
kaust.acknowledged.supportUnitOffice of Naval Research


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