Please use this identifier to cite or link to this item: doi:10.22028/D291-24868
Title: How to prefer more specific defaults in terminological default logic
Author(s): Baader, Franz
Hollunder, Bernhard
Language: English
Year of Publication: 1992
OPUS Source: Kaiserslautern ; Saarbrücken : DFKI, 1992
SWD key words: Künstliche Intelligenz
Formale Semantik
Terminologische Logik
DDC notations: 004 Computer science, internet
Publikation type: Report
Abstract: In a recent paper we have proposed terminological default logic as a formalism which combines both means for structured representation of classes and objects, and for default inheritance of properties. The major drawback which terminological default logic inherits from general default logic is that it does not take precedence of more specific defaults over more general ones into account. This behaviour has already been criticized in the general context of default logic, but it is all the more problematic in the terminological case where the emphasis lies on the hierarchical organization of concepts. The present paper addresses the problem of modifying terminological default logic such that more specific defaults are preferred. It turns out that the existing approaches for expressing priorities between defaults do not seem to be appropriate for this purpose. Therefore we shall consider an alternative approach for dealing with prioritization in the framework of Reiter's default logic. The formalism is presented in the general setting of default logic where priorities are given by an arbitrary partial ordering on the defaults. We shall exhibit some interesting properties of the new formalism, compare it with existing approaches, and describe an algorithm for computing extensions.
Link to this record: urn:nbn:de:bsz:291-scidok-36217
Series name: Research report / Deutsches Forschungszentrum für Künstliche Intelligenz [ISSN 0946-008x]
Series volume: 92-58
Date of registration: 22-Jun-2011
Faculty: SE - Sonstige Einrichtungen
Department: SE - DFKI Deutsches Forschungszentrum für Künstliche Intelligenz
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

Files for this record:
File Description SizeFormat 
RR_92_58.pdf15,83 MBAdobe PDFView/Open

Items in SciDok are protected by copyright, with all rights reserved, unless otherwise indicated.