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Journal of Automated Reasoning

dc.contributor.authorBundy, Alan
dc.date.accessioned2010-12-15T13:05:42Z
dc.date.available2010-12-15T13:05:42Z
dc.date.issued1986-06
dc.identifier.issn0168-7433en
dc.identifier.urihttp://www.springerlink.com/content/qu03231xq703381m/en
dc.identifier.urihttp://hdl.handle.net/1842/4526
dc.description.abstractIncidence Calculus is a technique for associating uncertainty values with logical sentences. These uncertainty values are called incidences and they are sets of points, which may be thought of as representing equivalence classes of situations, Tarskian models, or possible worlds. Incidence Calculus was originally introduced in [1]. Incidence Calculus was designed to overcome various inherent problems with purely numeric mechanisms for uncertain reasoning [2]. In particular, incidences can represent the dependence between sentences, which numbers cannot, and hence Incidence Calculus can provide genuine, probabilistic reasoning. In this paper we prove soundness and completeness results for some algorithms introduced in [1] and hence satisfy some of the correctness criteria for Incidence Calculus. These algorithms can be used for probabilistic reasoning and to check the consistency of the subjective probabilities of sentences.en
dc.language.isoenen
dc.publisherSpringerLinken
dc.subjectIncidence Calculusen
dc.subjectprobabilityen
dc.subjectuncertaintyen
dc.subjectinferenceen
dc.subjectlogicen
dc.subjectexpert systemsen
dc.titleCorrectness criteria of some algorithms for uncertain reasoning using Incidence Calculusen
dc.typeArticleen
dc.identifier.doi10.1007/BF02432147en
rps.issue2en
rps.volume2en
rps.titleJournal of Automated Reasoningen
dc.extent.pageNumbers109-126en
dc.date.updated2010-12-15T13:05:43Z
dc.identifier.eIssn1573-0670en


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