Multi-agent sequential hypothesis testing

Handle URI:
http://hdl.handle.net/10754/550514
Title:
Multi-agent sequential hypothesis testing
Authors:
Kim, Kwang-Ki K.; Shamma, Jeff S. ( 0000-0001-5638-9551 )
Abstract:
This 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.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Publisher:
IEEE
Journal:
Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
Conference/Event name:
Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
Issue Date:
15-Dec-2014
DOI:
10.1109/CDC.2014.7039682
Type:
Conference Paper
Additional Links:
http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7039682
Appears in Collections:
Conference Papers; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorKim, Kwang-Ki K.en
dc.contributor.authorShamma, Jeff S.en
dc.date.accessioned2015-04-23T14:15:07Zen
dc.date.available2015-04-23T14:15:07Zen
dc.date.issued2014-12-15en
dc.identifier.doi10.1109/CDC.2014.7039682en
dc.identifier.urihttp://hdl.handle.net/10754/550514en
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.en
dc.publisherIEEEen
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7039682en
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.en
dc.titleMulti-agent sequential hypothesis testingen
dc.typeConference Paperen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalDecision and Control (CDC), 2014 IEEE 53rd Annual Conference onen
dc.conference.date15-17 Dec. 2014en
dc.conference.nameDecision and Control (CDC), 2014 IEEE 53rd Annual Conference onen
dc.conference.locationLos Angeles, CAen
dc.eprint.versionPost-printen
dc.contributor.institutionSchool of Electrical and Computer Engineering, Georgia Institute of Technologyen
kaust.authorShamma, Jeff S.en
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