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dc.contributor.authorKakas, Antonis C.en
dc.contributor.authorLamma, E.en
dc.contributor.authorRiguzzi, F.en
dc.creatorKakas, Antonis C.en
dc.creatorLamma, E.en
dc.creatorRiguzzi, F.en
dc.date.accessioned2019-11-13T10:40:27Z
dc.date.available2019-11-13T10:40:27Z
dc.date.issued1998
dc.identifier.issn0302-9743
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/54126
dc.description.abstractWe present an approach for solving some of the problems of top-down Inductive Logic Programming systems when learning multiple predicates. The approach is based on an algorithm for learning abductive logic programs. Abduction is used to generate additional information that is useful for solving the problem of global inconsistency when learning multiple predicates.en
dc.source8th International Conference on Artificial Intelligence: Methodology, Systems, and Applications, AIMSA 1998en
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84867758281&partnerID=40&md5=a65a25cdffa5f254ad55af065b83ed18
dc.subjectArtificial intelligenceen
dc.subjectTopdownen
dc.subjectAbductive logic programsen
dc.subjectInductive logicen
dc.subjectMultiple predicatesen
dc.titleLearning multiple predicatesen
dc.typeinfo:eu-repo/semantics/article
dc.description.volume1480 LNAIen
dc.description.startingpage303
dc.description.endingpage316
dc.author.faculty002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Πληροφορικής / Department of Computer Science
dc.type.uhtypeArticleen
dc.description.notes<p>Sponsors: Eur. Coord. Comm. Artif. Intell. (ECCAI)en
dc.description.notesConference code: 93537en
dc.description.notesCited By :1</p>en
dc.source.abbreviationLect. Notes Comput. Sci.en
dc.contributor.orcidKakas, Antonis C. [0000-0001-6773-3944]
dc.gnosis.orcid0000-0001-6773-3944


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