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dc.contributor.authorYe, Mengbin
dc.contributor.authorLiu, J.
dc.contributor.authorWang, L.
dc.contributor.authorAnderson, B.D.O.
dc.contributor.authorCao, M.
dc.date.accessioned2021-07-06T12:32:12Z
dc.date.available2021-07-06T12:32:12Z
dc.date.issued2020
dc.identifier.citationYe, M. and Liu, J. and Wang, L. and Anderson, B.D.O. and Cao, M. 2020. Consensus and Disagreement of Heterogeneous Belief Systems in Influence Networks. IEEE Transactions on Automatic Control. 65 (11): pp. 4679-4694.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/84357
dc.identifier.doi10.1109/TAC.2019.2961998
dc.description.abstract

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.

dc.languageEnglish
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.sponsoredbyhttp://purl.org/au-research/grants/arc/DP160104500
dc.relation.sponsoredbyhttp://purl.org/au-research/grants/arc/DP190100887
dc.subjectScience & Technology
dc.subjectTechnology
dc.subjectAutomation & Control Systems
dc.subjectEngineering, Electrical & Electronic
dc.subjectEngineering
dc.subjectCultural differences
dc.subjectLimiting
dc.subjectSystematics
dc.subjectIndexes
dc.subjectSocial networking (online)
dc.subjectAustralia
dc.subjectStability analysis
dc.subjectAgent-based models
dc.subjectinfluence networks
dc.subjectmultiagent systems
dc.subjectopinion dynamics
dc.subjectsocial networks
dc.subjectOPINION DYNAMICS
dc.subjectTUTORIAL
dc.subjectMODELS
dc.titleConsensus and Disagreement of Heterogeneous Belief Systems in Influence Networks
dc.typeJournal Article
dcterms.source.volume65
dcterms.source.number11
dcterms.source.startPage4679
dcterms.source.endPage4694
dcterms.source.issn0018-9286
dcterms.source.titleIEEE Transactions on Automatic Control
dc.date.updated2021-07-06T12:32:09Z
curtin.note

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

curtin.departmentSchool of Electrical Engineering, Computing and Mathematical Sciences (EECMS)
curtin.accessStatusOpen access
curtin.facultyFaculty of Science and Engineering
curtin.contributor.orcidYe, Mengbin [0000-0003-1698-0173]
dcterms.source.eissn1558-2523
curtin.contributor.scopusauthoridYe, Mengbin [56203529600]


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