Importance-based semantics of polynomial comparative preference inference

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dc.contributor.author Wilson, Nic
dc.contributor.editor De Raedt, Luc
dc.contributor.editor Bessiere, Christian
dc.contributor.editor Dubois, Didier
dc.contributor.editor Doherty, Patrick
dc.contributor.editor Frasconi, Paolo
dc.contributor.editor Heintz, Fredrik
dc.contributor.editor Lucas, Peter
dc.date.accessioned 2014-02-17T12:36:19Z
dc.date.available 2014-02-17T12:36:19Z
dc.date.copyright 2012
dc.date.issued 2012
dc.identifier.citation WILSON, N. 2012. Importance-based semantics of polynomial comparative preference inference. In: DE RAEDT, L., BESSIERE, C., DUBOIS, D., DOHERTY, P., FRASCONI, P., HEINTZ, F. & LUCAS, P. (eds.) ECAI 2012: 20th European Conference on Artificial Intelligence. Montpellier, France, 27-31 August. Amsterdam: IOS Press, pp. 852-857. doi: 10.3233/978-1-61499-098-7-852 en
dc.identifier.startpage 852 en
dc.identifier.endpage 857 en
dc.identifier.isbn 978-1-61499-097-0
dc.identifier.isbn 978-1-61499-098-7
dc.identifier.uri http://hdl.handle.net/10468/1386
dc.identifier.doi 10.3233/978-1-61499-098-7-852
dc.description.abstract A basic task in preference reasoning is inferring a preference between a pair of outcomes (alternatives) from an input set of preference statements. This preference inference task for comparative preferences has been shown to be computationally very hard for the standard kind of inference. Recently, a new kind of preference inference has been developed, which is polynomial for relatively expressive preference languages, and has the additional property of being much less conservative; this can be a major advantage, since it will tend to make the number of undominated outcomes smaller. It derives from a semantics where models are weak orders that are generated by objects called cp-trees, which represent a kind of conditional lexicographic order. We show that there are simple conditions, based on the notion of importance, that determine whether a weak order can be generated by a cp-tree of the given form. This enables a simple characterisation of the less conservative preference inference. We go on to study the importance properties satisfied by a simple kind of cp-tree, leading to another characterisation of the corresponding preference inference. en
dc.description.uri http://www2.lirmm.fr/ecai2012/ en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher IOS Press en
dc.relation.ispartof Proc. European Conference on Artificial Intelligence (ECAI 2012)
dc.relation.ispartofseries Frontiers in Artificial Intelligence and Applications;242
dc.relation.uri http://ebooks.iospress.nl/publication/7081
dc.rights © 2012 The Author. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License. en
dc.rights.uri http://creativecommons.org/licenses/by-nc/2.0/ en
dc.subject Preference reasoning en
dc.subject Preference statements en
dc.subject Preference inference en
dc.subject CP-trees en
dc.subject.lcsh Computer science en
dc.title Importance-based semantics of polynomial comparative preference inference en
dc.type Conference item en
dc.internal.authorurl http://research.ucc.ie/profiles/D005/nwilson en
dc.internal.authorcontactother Nic Wilson, Computer Science, University College Cork, Cork, Ireland. +353-21-490-3000 Email: n.wilson@4c.ucc.ie en
dc.internal.availability Full text available en
dc.date.updated 2012-12-20T18:12:44Z
dc.description.version Accepted Version en
dc.internal.rssid 185131882
dc.contributor.funder Science Foundation Ireland en
dc.description.status Peer reviewed en
dc.internal.copyrightchecked No !!CORA!! Creative Commons Licence en
dc.internal.licenseacceptance Yes en
dc.internal.conferencelocation Montpellier, France. en
dc.internal.placepublication Amsterdam en
dc.internal.IRISemailaddress n.wilson@ucc.ie en
dc.relation.project info:eu-repo/grantAgreement/SFI/SFI Principal Investigator Programme (PI)/08/IN.1/I1912/IE/The Development of Artificial intelligence Approaches for Preferences in Combinational Problems/ en


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© 2012 The Author. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License. Except where otherwise noted, this item's license is described as © 2012 The Author. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License.
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