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dc.contributor.authorKim, Kwang-Ki K.
dc.contributor.authorShamma, Jeff S.
dc.date.accessioned2015-04-23T14:15:07Z
dc.date.available2015-04-23T14:15:07Z
dc.date.issued2015-02-17
dc.identifier.citationKim, K.-K. K., & Shamma, J. S. (2014). Multi-agent sequential hypothesis testing. 53rd IEEE Conference on Decision and Control. doi:10.1109/cdc.2014.7039682
dc.identifier.doi10.1109/CDC.2014.7039682 WOS:000370073802015
dc.identifier.urihttp://hdl.handle.net/10754/550514
dc.description.abstractThis paper considers multi-agent sequential hypothesis testing and presents a framework for strategic learning in sequential games with explicit consideration of both temporal and spatial coordination. The associated Bayes risk functions explicitly incorporate costs of taking private/public measurements, costs of time-difference and disagreement in actions of agents, and costs of false declaration/choices in the sequential hypothesis testing. The corresponding sequential decision processes have well-defined value functions with respect to (a) the belief states for the case of conditional independent private noisy measurements that are also assumed to be independent identically distributed over time, and (b) the information states for the case of correlated private noisy measurements. A sequential investment game of strategic coordination and delay is also discussed as an application of the proposed strategic learning rules.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7039682
dc.rights(c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
dc.titleMulti-agent sequential hypothesis testing
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentElectrical Engineering Program
dc.contributor.departmentRISC Laboratory
dc.identifier.journal53rd IEEE Conference on Decision and Control
dc.conference.date15-17 Dec. 2014
dc.conference.nameDecision and Control (CDC), 2014 IEEE 53rd Annual Conference on
dc.conference.locationLos Angeles, CA
dc.eprint.versionPost-print
dc.contributor.institutionSchool of Electrical and Computer Engineering, Georgia Institute of Technology
kaust.personShamma, Jeff S.
refterms.dateFOA2018-06-14T04:57:25Z
dc.date.published-online2015-02-17
dc.date.published-print2014-12


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