Bitte benutzen Sie diese Referenz, um auf diese Ressource zu verweisen: doi:10.22028/D291-25213
Titel: Attributive description formalisms and the rest of the world
VerfasserIn: Nebel, Bernhard
Smolka, Gert
Sprache: Englisch
Erscheinungsjahr: 1991
Kontrollierte Schlagwörter: Künstliche Intelligenz
DDC-Sachgruppe: 004 Informatik
Dokumenttyp: Forschungsbericht (Report zu Forschungsprojekten)
Abstract: Research in knowledge representation has led to the development of so-called terminological logics, which have the purpose to support the representation of the conceptual and terminological part of Artificial Intelligence applications. Independently, in Computational Linguistics so-called feature logics have been developed, which are aimed at representing the semantic and syntactic information natural language sentences convey. Since both of these logics rely mainly on attributes as the primary notational primitives for representing knowledge, they can be jointly characterized as attributive description formalisms. Although the intended applications for terminological logics and feature are not identical, and the computational services of systems based on the respective formalisms are quite different for this reason, the logical foundations turn out to be very similar - as we pointed out elsewhere. In this paper, we will show how attributive description formalisms relate to "the rest of the world." Recently, a number of formal results in the area of attributive description formalisms have been obtained by exploiting other research fields, such as formal language theory, automata theory, and modal logics. This connection between different fields of formal research will be highlighted in the sequel.
Link zu diesem Datensatz: urn:nbn:de:bsz:291-scidok-50135
hdl:20.500.11880/25269
http://dx.doi.org/10.22028/D291-25213
Schriftenreihe: Research report / Deutsches Forschungszentrum für Künstliche Intelligenz [ISSN 0946-008x]
Band: 91-15
Datum des Eintrags: 5-Dez-2012
Fakultät: SE - Sonstige Einrichtungen
Fachrichtung: SE - DFKI Deutsches Forschungszentrum für Künstliche Intelligenz
Sammlung:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

Dateien zu diesem Datensatz:
Datei Beschreibung GrößeFormat 
RR_91_15_.pdf1,19 MBAdobe PDFÖffnen/Anzeigen


Alle Ressourcen in diesem Repository sind urheberrechtlich geschützt.