Consensus in opinion dynamics as a repeated game

Dario Bauso*, Mark Cannon

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

15 Citations (Scopus)
13 Downloads (Pure)

Abstract

We study an n-agent averaging process with dynamics subject to controls and adversarial disturbances. The model arises in multi-population opinion dynamics with macroscopic and microscopic intertwined dynamics. The averaging process describes the influence from neighbouring populations, whereas the input term indicates how the distribution of opinions in the population changes as a result of dynamical evolutions at a microscopic level (individuals' changing opinions). The input term is obtained as the vector payoff of a two player repeated game. We study conditions under which the agents achieve robust consensus to some predefined target set. Such conditions build upon the approachability principle in repeated games with vector payoffs. (C) 2018 Elsevier Ltd. All rights reserved.

Original languageEnglish
Pages (from-to)204-211
Number of pages8
JournalAutomatica
Volume90
DOIs
Publication statusPublished - Apr-2018
Externally publishedYes

Keywords

  • Game theory
  • Networks
  • Allocations
  • Robust receding horizon control
  • NETWORKED MULTIAGENT SYSTEMS
  • MODEL

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