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 |
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dc.identifier.uri |
http://hdl.handle.net/10468/10801 |
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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 |
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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 |
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dc.type |
Conference item |
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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 |
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dc.description.version |
Accepted Version |
en |
dc.internal.rssid |
542655621 |
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dc.contributor.funder |
Science Foundation Ireland
|
en |
dc.description.status |
Peer reviewed |
en |
dc.internal.copyrightchecked |
No |
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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 |