Reaching Bayesian consensus in cognitive systems by decision exchanges

Yunlong Wang, Petar M. Djuric

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

2 Scopus citations

Abstract

We consider the problem of distributed Bayesian hypothesis testing on a set of time invariant hypotheses in a cognitive system of cooperative agents. Each agent in the system obtains one set of private observations and then at every time slot two randomly selected agents repeatedly exchange their decisions and update their beliefs. We propose a method that allows the agents to reach an optimal local consensus by just exchanging decisions. It can be shown that with this strategy, all agents in the system can achieve a consensus in decision, which is also the global optimal decision held by a fictitious fusion center. We provide performance and convergence analysis of the proposed method as well as simulation results that demonstrate its asymptotical properties.

Original languageEnglish (US)
Title of host publication2013 Proceedings of the 21st European Signal Processing Conference, EUSIPCO 2013
PublisherEuropean Signal Processing Conference, EUSIPCO
ISBN (Print)9780992862602
StatePublished - Jan 1 2013
Event2013 21st European Signal Processing Conference, EUSIPCO 2013 - Marrakech, Morocco
Duration: Sep 9 2013Sep 13 2013

Other

Other2013 21st European Signal Processing Conference, EUSIPCO 2013
CountryMorocco
CityMarrakech
Period9/9/139/13/13

Keywords

  • Bayesian consensus
  • Cognitive system
  • cooperative agents
  • distributed hypothesis testing

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    Wang, Y., & Djuric, P. M. (2013). Reaching Bayesian consensus in cognitive systems by decision exchanges. In 2013 Proceedings of the 21st European Signal Processing Conference, EUSIPCO 2013 [6811808] European Signal Processing Conference, EUSIPCO.