Consensus and Disagreement of Heterogeneous Belief Systems in Influence Networks

Ye, B., Liu, J., Wang, L., Anderson, B. D. O. & Cao, M., 1-Nov-2020, In : IEEE-Transactions on Automatic Control. 65, 11, p. 4679-4694 16 p., 8941271.

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Recently, an opinion dynamics model has been proposed to describe a network of individuals discussing a set of logically interdependent topics. For each individual, the set of topics and the logical interdependencies between the topics (captured by a logic matrix) form a belief system. We investigate the role the logic matrix and its structure plays in determining the final opinions, including existence of the limiting opinions, of a strongly connected network of individuals. We provide a set of results that, given a set of individuals' belief systems, allow a systematic determination of which topics will reach a consensus, and of which topics will disagreement arise. For irreducible logic matrices, each topic reaches a consensus. For reducible logic matrices, which indicates a cascade interdependence relationship, conditions are given on whether a topic will reach a consensus or not. It turns out that heterogeneity among the individuals' logic matrices, and a cascade interdependence relationship, are necessary conditions for disagreement. Thus, this article attributes for the first time, a strong diversity of limiting opinions to heterogeneity of belief systems in influence networks, in addition to the more typical explanation that strong diversity arises from individual stubbornness.

Original languageEnglish
Article number8941271
Pages (from-to)4679-4694
Number of pages16
JournalIEEE-Transactions on Automatic Control
Issue number11
Publication statusPublished - 1-Nov-2020
Event IEEE Transactions on Automatic Control -
Duration: 24-Dec-201924-Dec-2019


IEEE Transactions on Automatic Control


Event: Conference


  • Agent-based models, influence networks, multiagent systems, opinion dynamics, social networks

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