Multi-agent sequential hypothesis testing

Kwang-Ki K. Kim, Jeff S. Shamma

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations


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.
Original languageEnglish (US)
Title of host publication53rd IEEE Conference on Decision and Control
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages6
ISBN (Print)9781467360906
StatePublished - Feb 17 2015
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01


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