Combining two choice functions and enforcing natural properties

Show simple item record Wilson, Nic 2021-02-23T14:26:05Z 2021-02-23T14:26:05Z 2020-08
dc.identifier.citation Wilson, N. (2020) 'Combining Two Choice Functions and Enforcing Natural Properties' M-PREF2020: 12th Multidisciplinary Workshop on Advances in Preference Handling, ECAI 2020, Santiago de Compostela, Spain, (online) 29 August - 8 September. en
dc.identifier.startpage 1 en
dc.identifier.endpage 8 en
dc.description.abstract This paper considers the problem of combining two choice functions (CFs), or setwise optimisation functions, based on use of intersection and composition. Each choice function represents preference information for an agent, saying, for any subset of a set of alternatives, which are the preferred, and which are the sub-optimal alternatives. The aim is to find a combination operation that maintains good properties of the choice function. We consider a family of natural properties of CFs, and analyse which hold for different classes of CF. We determine relationships between intersection and composition operations, and find out which properties are maintained by these combination rules. We go on to show how the most important of the CF properties can be enforced or restored, and use this kind of procedure to define combination operations that then maintain the desirable properties. en
dc.description.sponsorship Science Foundation Ireland (under Grant No. 12/RC/2289 and Grant No. 12/RC/2289-P2 which are co-funded under the European Regional Development Fund) en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher M-PREF2020
dc.rights © 2020 the author
dc.subject Choice functions (CFs) en
dc.subject Combination operations en
dc.subject Preference inputs en
dc.subject Binary relations en
dc.title Combining two choice functions and enforcing natural properties en
dc.title.alternative Combining social choice functions en
dc.type Conference item en
dc.internal.authorcontactother Nic Wilson, Computer Science, University College Cork, Cork, Ireland. +353-21-490-3000 Email: en
dc.internal.availability Full text available en 2021-02-23T14:05:08Z
dc.description.version Accepted Version en
dc.internal.rssid 556244254
dc.contributor.funder Science Foundation Ireland en
dc.contributor.funder European Regional Development Fund en
dc.description.status Peer reviewed en
dc.internal.copyrightchecked Yes
dc.internal.licenseacceptance Yes en
dc.internal.conferencelocation Santiago de Compostela, Spain (Virtual) en
dc.internal.IRISemailaddress en
dc.internal.bibliocheck In Press. Check for future publication 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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