Opinion dynamics in social networks through mean-field games

D. Bauso, H. Tembine, T. Başar

Research output: Contribution to journalArticle

Abstract

Emulation, mimicry, and herding behaviors are phenomena that are observed when multiple social groups interact. To study such phenomena, we consider in this paper a large population of homogeneous social networks. Each such network is characterized by a vector state, a vector-valued controlled input, and a vector-valued exogenous disturbance. The controlled input of each network aims to align its state to the mean distribution of other networks' states in spite of the actions of the disturbance. One of the contributions of this paper is a detailed analysis of the resulting mean-field game for the cases of both polytopic and L2 bounds on controls and disturbances. A second contribution is the establishment of a robust mean-field equilibrium, that is, a solution including the worst-case value function, the state feedback best-responses for the controlled inputs and worst-case disturbances, and a density evolution. This solution is characterized by the property that no player can benefit from a unilateral deviation even in the presence of the disturbance. As a third contribution, microscopic and macroscopic analyses are carried out to show convergence properties of the population distribution using stochastic stability theory.

Original languageEnglish (US)
Pages (from-to)3225-3257
Number of pages33
JournalSIAM Journal on Control and Optimization
Volume54
Issue number6
DOIs
StatePublished - Jan 1 2016

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Keywords

  • Mean-field games
  • Opinion dynamics
  • Stochastic stability

ASJC Scopus subject areas

  • Control and Optimization
  • Applied Mathematics

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