Uncertain linear constraints

dc.contributor.authorWilson, Nic
dc.date.accessioned2020-11-16T14:02:37Z
dc.date.available2020-11-16T14:02:37Z
dc.date.issued2004-08
dc.date.updated2020-11-04T13:33:13Z
dc.description.abstractLinear constraints occur naturally in many reasoning problems and the information that they represent is often uncertain. There is a difficulty in applying many AI uncertainty formalisms to this situation, as their representation of the underlying logic, either as a mutually exclusive and exhaustive set of possibilities, or with a propositional or a predicate logic, is inappropriate (or at least unhelpful). To overcome this, we express reasoning with linear constraints as a logic, and develop the formalisms based on this different underlying logic. We focus in particular on a possibilistic logic representation of uncertain linear constraints, a lattice-valued possibilistic logic, and a Dempster-Shafer representation.en
dc.description.statusPeer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationWilson, Nic; (2004) 'Uncertain Linear Constraints ', ECAI' 04: Proceedings of the 16th European Conference on Artificial Intelligence, 22- 27 August, Valencia, Spain: IOS Press, pp. 231-235.en
dc.identifier.endpage235en
dc.identifier.startpage231en
dc.identifier.urihttps://hdl.handle.net/10468/10763
dc.language.isoenen
dc.publisherIOS Pressen
dc.relation.urihttps://www.iospress.nl/book/ecai-2004/
dc.rights© 2004 IOS Pressen
dc.subjectConstraintsen
dc.subjectLogicen
dc.subjectLinear constraintsen
dc.subjectAI uncertainty formalismsen
dc.titleUncertain linear constraintsen
dc.typeConference itemen
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