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dc.contributor.authorZha, Quanbo
dc.contributor.authorDong, Yucheng
dc.contributor.authorZhang, Hengjie
dc.contributor.authorChiclana, Francisco
dc.contributor.authorHerrera-Viedma, Enrique
dc.contributor.authorHerrera-Viedma
dc.date.accessioned2019-10-30T15:49:05Z
dc.date.available2019-10-30T15:49:05Z
dc.date.issued2019-10-28
dc.identifier.citationZha, Q., Dong, Y., Zhang, H., Chiclana, F., Herrera-Viedma, E. (2019) A Personalized Feedback Mechanism based on Bounded Confidence to Support Consensus Reaching in Group Decision Making. IEEE Transactions on Systems, Man and Cybernetics: Systems.en
dc.identifier.issn2168-2216
dc.identifier.urihttps://dora.dmu.ac.uk/handle/2086/18676
dc.descriptionThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.en
dc.description.abstractDifferent feedback mechanisms have been reported in consensus reaching models to provide advices for preference adjustment to assist decision makers to improve their consensus levels. However, most feedback mechanisms do not consider the willingness of decision makers to accept these advices. In the opinion dynamics discipline, the bounded confidence model justifies well that in the process of interaction a decision maker only considers the preferences that do not exceed a certain confidence level compared to his own preference. Inspired by this idea, this article proposes a new consensus reaching model with personalized feedback mechanism to help decision makers with bounded confidences in achieving consensus. Specifically, the personalized feedback mechanism produces more acceptable advices in the two cases where bounded confidences are known or unknown, and the unknown ones are estimated by a learning algorithm. Finally, numerical example and simulation analysis are presented to explore the effectiveness of the proposed model in reaching consensus.en
dc.language.isoenen
dc.publisherIEEEen
dc.subjectBounded confidence learningen
dc.subjectgroup decision making (GDM)en
dc.subjectpersonalized feedback mechanismen
dc.subjectpreference relationen
dc.subjectsoft consensus.en
dc.titleA Personalized Feedback Mechanism based on Bounded Confidence to Support Consensus Reaching in Group Decision Makingen
dc.typeArticleen
dc.identifier.doihttps://doi.org/10.1109/tsmc.2019.2945922
dc.peerreviewedYesen
dc.funderOther external funder (please detail below)en
dc.projectidGrant 71571124, Grant 71871149, and Grant 71801081en
dc.projectidGrant sksyl201705 and Grant 2018hhs-58en
dc.projectidGrant 18YJC630240en
dc.projectidGrant TIN2016-75850-Ren
dc.cclicenceCC-BY-NCen
dc.date.acceptance2019-09-25
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en
dc.funder.otherNSF of Chinaen
dc.funder.otherSichuan Universityen
dc.funder.otherChinese Ministry of Educationen
dc.funder.otherFEDER Fundsen


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