Voting rules from random relations

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dc.contributor.author Wilson, Nic
dc.date.accessioned 2020-12-02T13:26:13Z
dc.date.available 2020-12-02T13:26:13Z
dc.date.issued 2020-08
dc.identifier.citation Wilson, N. (2020) 'Voting Rules from Random Relations', ECAI 2020 - 24th European Conference on Artificial Intelligence, Santiago de Compostela, Spain, 29 Aug. - 8 Sept., Frontiers in Artificial Intelligence and Applications, vol. 325, pp. 235-242. doi: 10.3233/FAIA200098 en
dc.identifier.volume 325 en
dc.identifier.startpage 235 en
dc.identifier.endpage 242 en
dc.identifier.isbn 978-1-64368-100-9
dc.identifier.isbn 978-1-64368-101-6
dc.identifier.uri http://hdl.handle.net/10468/10805
dc.identifier.doi 10.3233/FAIA200098 en
dc.description.abstract We consider a way of generating voting rules based on a random relation, the winners being alternatives that have the highest probability of being supported. We define different notions of support, such as whether an alternative dominates the other alternatives, or whether an alternative is undominated, and we consider structural assumptions on the form of the random relation, such as being acyclic, asymmetric, connex or transitive. We give sufficient conditions on the supporting function for the associated voting rule to satisfy various properties such as Pareto and monotonicity. The random generation scheme involves a parameter p between zero and one. Further voting rules are obtained by tending p to zero, and by tending p to one, and these limiting rules satisfy a homogeneity property, and, in certain cases, Condorcet consistency. We define a language of supporting functions based on eight natural properties, and categorise the different rules that can be generated for the limiting p cases. en
dc.description.sponsorship Science Foundation Ireland (Grant No. 12/RC/2289 and Grant No. 12/RC/2289-P2, co-funded under the European Regional Development Fund) en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher IOS Press en
dc.relation.uri http://ebooks.iospress.nl/volumearticle/54893
dc.rights © 2020 The authors and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0). en
dc.rights.uri https://creativecommons.org/licenses/by-nc/4.0/deed.en_US en
dc.subject Random generation en
dc.subject Voting rules en
dc.subject Artificial intelligence (AI) en
dc.title Voting rules from random relations en
dc.type Conference item en
dc.internal.authorcontactother Nic Wilson, Computer Science, University College Cork, Cork, Ireland. +353-21-490-3000 Email: n.wilson@ucc.ie en
dc.internal.availability Full text available en
dc.date.updated 2020-11-04T12:17:26Z
dc.description.version Published Version en
dc.internal.rssid 542655605
dc.contributor.funder Science Foundation Ireland en
dc.contributor.funder European Regional Development Fund en
dc.description.status Peer reviewed en
dc.identifier.journaltitle Frontiers in Artificial Intelligence and Applications, ECAI 2020 en
dc.internal.copyrightchecked No
dc.internal.licenseacceptance Yes en
dc.internal.conferencelocation Santiago de Compostela, Spain en
dc.internal.IRISemailaddress n.wilson@ucc.ie en
dc.relation.project info:eu-repo/grantAgreement/SFI/SFI Research Centres/12/RC/2289/IE/INSIGHT - Irelands Big Data and Analytics Research Centre/ en


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© 2020 The authors and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0). Except where otherwise noted, this item's license is described as © 2020 The authors and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).
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