Learning in network games with incomplete information: Asymptotic analysis and tractable implementation of rational behavior

Ceyhun Eksin*, Pooya Molavi, Alejandro Ribeiro, Ali Jadbabaie

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

The role of social networks in learning and opinion formation has been demonstrated in a variety of scenarios such as the dynamics of technology adoption [1], consumption behavior [2], organizational behavior [3], and financial markets [4]. The emergence of network-wide social phenomena from local interactions between connected agents has been studied using field data [5]?[7] as well as lab experiments [8], [9]. Interest in opinion dynamics over networks is further amplified by the continuous growth in the amount of time that individuals spend on social media Web sites and the consequent increase in the importance of networked phenomena in social and economic outcomes. As quantitative data become more readily available, a research problem is to identify metrics that could characterize emergent phenomena such as conformism or diversity in individuals? preferences for consumer products or political ideologies [10]. With these metrics available, a natural follow-up research goal is the study of mechanisms that lead to diversity or conformism and the role of network properties like neighborhood structures on these outcomes. All of these questions motivate the development of theoretical models of opinion formation through local interactions in different scenarios.

Original languageEnglish (US)
Article number6494686
Pages (from-to)30-42
Number of pages13
JournalIEEE Signal Processing Magazine
Volume30
Issue number3
DOIs
StatePublished - Jan 1 2013

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics

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