Computation and complexity of preference inference based on hierarchical models

dc.contributor.authorWilson, Nicen
dc.contributor.authorGeorge, Anne-Marieen
dc.contributor.authorO'Sullivan, Barryen
dc.contributor.funderScience Foundation Irelanden
dc.date.accessioned2025-04-23T15:04:33Z
dc.date.available2025-04-23T15:04:33Z
dc.date.issued2024en
dc.description.abstractPreference Inference involves inferring additional user preferences from elicited or observed preferences, based on assumptions regarding the form of the user's preference relation. In this paper we consider a situation in which alternatives have an associated vector of costs, each component corresponding to a different criterion, and are compared using a kind of lexicographic order, similar to the way alternatives are compared in a Hierarchical Constraint Logic Programming model. It is assumed that the user has some (unknown) importance ordering on criteria, and that to compare two alternatives, firstly, the combined cost of each alternative with respect to the most important criteria are compared; only if these combined costs are equal, are the next most important criteria considered. The preference inference problem then consists of determining whether a preference statement can be inferred from a set of input preferences. We show that this problem is coNP-complete, even if one restricts the cardinality of the equal-importance sets to have at most two elements, and one only considers non-strict preferences. However, it is polynomial if it is assumed that the user's ordering of criteria is a total ordering; it is also polynomial if the sets of equally important criteria are all equivalence classes of a given fixed equivalence relation. We give an efficient polynomial algorithm for these cases, which also throws light on the structure of the inference.en
dc.description.statusPeer revieweden
dc.description.versionPublished Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationWilson, N., George, A.-M. and O’Sullivan, B. (2024) ‘Computation and complexity of preference inference based on hierarchical models’. arXiv. https://doi.org/10.48550/ARXIV.2409.11044en
dc.identifier.doihttps://doi.org/10.48550/ARXIV.2409.11044en
dc.identifier.endpage11en
dc.identifier.startpage1en
dc.identifier.urihttps://hdl.handle.net/10468/17309
dc.language.isoenen
dc.publisherarXiven
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/Research Centres Programme/12/RC/2289/IE/INSIGHT - Irelands Big Data and Analytics Research Centre/en
dc.relation.urihttps://arxiv.org/abs/2409.11044en
dc.rights© 2024, the Authors.en
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subjectPreference inferenceen
dc.subjectUser's preference relationen
dc.subjectHierarchical Constraint Logic Programming modelen
dc.titleComputation and complexity of preference inference based on hierarchical modelsen
dc.typeArticle (peer-reviewed)en
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