Efficient inference and computation of optimal alternatives for preference languages based on lexicographic models

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dc.contributor.author Wilson, Nic
dc.contributor.author George, Anne-Marie
dc.date.accessioned 2020-12-01T17:05:59Z
dc.date.available 2020-12-01T17:05:59Z
dc.date.issued 2017-08
dc.identifier.citation Wilson, N. and George, A.-M. (2017) 'Efficient Inference and Computation of Optimal Alternatives for Preference Languages Based On Lexicographic Models', IJCAI'17: Proceedings of the 26th International Joint Conference on Artificial Intelligence, Melbourne, Australia 19-25 August, pp. 1311-1317. doi: 10.24963/ijcai.2017/182 en
dc.identifier.startpage 1311 en
dc.identifier.endpage 1317 en
dc.identifier.isbn 978-0-9992411-0-3
dc.identifier.uri http://hdl.handle.net/10468/10801
dc.identifier.doi 10.24963/ijcai.2017/182 en
dc.description.abstract We analyse preference inference, through consistency, for general preference languages based on lexicographic models. We identify a property, which we call strong compositionality , that applies for many natural kinds of preference statement, and that allows a greedy algorithm for determining consistency of a set of preference statements. We also consider different natural definitions of optimality, and their relations to each other, for general preference languages based on lexicographic models. Based on our framework, we show that testing consistency, and thus inference, is polynomial for a specific preference language L′ pqT , which allows strict and non-strict statements, comparisons between outcomes and between partial tuples, both ceteris paribus and strong statements, and their combination. Computing different kinds of optimal sets is also shown to be polynomial; this is backed up by our experimental results. en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher International Joint Conferences on Artificial Intelligence en
dc.relation.uri https://www.ijcai.org/Proceedings/2017/182
dc.rights © 2017 International Joint Conferences on Artificial Intelligence en
dc.subject Preference inference techniques en
dc.subject Preference inference en
dc.subject Artificial intelligence (AI) en
dc.subject AI technology en
dc.subject Knowledge representation en
dc.subject Reasoning and logic: preferences en
dc.title Efficient inference and computation of optimal alternatives for preference languages based on lexicographic models 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 2020-11-04T13:05:29Z
dc.description.version Accepted Version en
dc.internal.rssid 542655621
dc.contributor.funder Science Foundation Ireland en
dc.description.status Peer reviewed en
dc.internal.copyrightchecked No
dc.internal.licenseacceptance Yes en
dc.internal.conferencelocation Melbourne, Australia 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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