A note on paraconsistent entailment in machine learning

dc.contributor.authorBell, Siegfriedde
dc.contributor.authorWeber, Steffode
dc.date.accessioned2004-12-06T12:53:30Z
dc.date.available2004-12-06T12:53:30Z
dc.date.created1994de
dc.date.issued1999-10-27de
dc.description.abstractRecent publications witness that there is a growing interest in multi-valued logics for machine learning; some of them arose as a more or less formal description of a computer program's inferential behaviour. The referred origin of these systems is Belnap's fourvalued logic, which has been adopted for the various needs of knowledge representation in a machine learning system. However, it is unclear what an inconsistent knowledge base entails. We investigate Mobal's logic < and show how to interpret the term `paraconsistent inference' of this system. It turns out that the meaning of the basic connective ! of < can be represented as a combination of two systems of Kleene's strong three-valued logic, where the two systems differ in the set of designated truth values. The resulting logic is functionally complete but the entailment relation is not axiomatizable. This drawback yields a fundamental difference between nonmontonicity within belief-revision and non-monotonic reasoning systems like Servi's refinement 1 of Gabbay's .en
dc.format.extent258634 bytes
dc.format.extent718982 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/postscript
dc.identifier.issn0943-4135de
dc.identifier.urihttp://hdl.handle.net/2003/2579
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-14890
dc.language.isoende
dc.publisherUniversität Dortmundde
dc.relation.ispartofseriesForschungsberichte des Lehrstuhls VIII, Fachbereich Informatik der Universität Dortmund ; 10de
dc.subject.ddc004de
dc.titleA note on paraconsistent entailment in machine learningen
dc.typeTextde
dc.type.publicationtypereport
dcterms.accessRightsopen access

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