Extending uncertainty formalisms to linear constraints and other complex formalisms

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dc.contributor.authorWilson, Nic
dc.contributor.funderScience Foundation Irelanden
dc.date.accessioned2013-05-13T14:00:18Z
dc.date.available2013-05-13T14:00:18Z
dc.date.copyright2008
dc.date.issued2008-08
dc.date.updated2012-12-20T17:41:36Z
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 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 difficulty, 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, an assumption-based reasoning formalism and a Dempster-Shafer representation, proving some fundamental results for these extended systems. Our results on extending uncertainty formalisms also apply to a very general class of underlying monotonic logics.en
dc.description.sponsorshipScience Foundation Ireland (00/PI.1/C075); Science Foundation Ireland (05/IN/I886)en
dc.description.statusPeer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationWilson, N; (2008) 'Extending uncertainty formalisms to linear constraints and other complex formalisms'. International Journal of Approximate Reasoning, 49 (1): 83-98. doi: 10.1016/j.ijar.2007.08.007en
dc.identifier.doi10.1016/j.ijar.2007.08.007
dc.identifier.endpage98en
dc.identifier.issued1en
dc.identifier.journaltitleInternational Journal of Approximate Reasoningen
dc.identifier.startpage83en
dc.identifier.urihttps://hdl.handle.net/10468/1118
dc.identifier.volume49en
dc.language.isoenen
dc.publisherElsevieren
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Principal Investigator Programme (PI)/00/PI.1/C075/IE/Constraint Computation: Automation and Application/
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Technology and Innovation Development Award (TIDA)/05/IN.1/I886 TIDA 09/IE/Costraint Baset Energy Cost Efficient Scheduling/
dc.relation.urihttp://www.sciencedirect.com/science/article/pii/S0888613X07001235
dc.rights(c) 2007 Published by Elsevier Inc. NOTICE: this is the author’s version of a work that was accepted for publication in International Journal of Approximate Reasoning. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Journal of Approximate Reasoning, [VOL 49, ISSUE 1, (2008)] DOI: http://dx.doi.org/10.1016/j.ijar.2007.08.007en
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectDempster-Shafer theoryen
dc.subjectPossibilistic logicen
dc.subjectLattice-valued possibilistic logicen
dc.subjectAssumption-based reasoningen
dc.subjectLinear constraintsen
dc.subjectSpatial and temporal reasoningen
dc.subjectNetworksen
dc.subject.lcshComputer science.en
dc.titleExtending uncertainty formalisms to linear constraints and other complex formalismsen
dc.typeArticle (peer-reviewed)en
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