Opinion dynamics in multi-agent systems with binary decision exchanges

Yunlong Wang, Lingqing Gan, Petar M. Djuric

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

1 Scopus citations

Abstract

Opinion dynamics in social networks has been widely studied in recent years, mostly by considering exchanges of opinions among neighboring agents. This paper addresses a scenario where the agents make decisions repeatedly on two hypotheses and where agents only exchange decisions. Motivated by the Bayesian models in the literature of human cognition, we model this learning procedure by the Bayes' rule. The social belief of each agent is defined to be the posterior of one of the hypotheses conditioned on the information it obtained from the society. We show that under certain conditions, once the social belief evolves to some region, the agent will refuse to change its belief. We demonstrate the asymptotical properties of the proposed model by computer simulations.

Original languageEnglish (US)
Title of host publication2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4588-4592
Number of pages5
ISBN (Electronic)9781479999880
DOIs
StatePublished - May 18 2016
Event41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Shanghai, China
Duration: Mar 20 2016Mar 25 2016

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2016-May
ISSN (Print)1520-6149

Other

Other41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016
Country/TerritoryChina
CityShanghai
Period3/20/163/25/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

  • Bayesian learning
  • Opinion dynamics
  • voter model

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