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A Non-monotonic Description Logic of Typicality

Authors: L. GIORDANO; GLIOZZI, Valentina; N. OLIVETTI; POZZATO, GIAN LUCA;

A Non-monotonic Description Logic of Typicality

Abstract

n this paper we propose a nonmonotonic extension ALC + Tmin of the Description Logic ALC for reasoning about prototypical properties and inheritance with exception. The logic ALC + Tmin is built upon a previously introduced (monotonic) logic ALC + T, that is obtained by adding a typicality operator T to ALC. The operator T is intended to select the “most normal” or “most typical” instances of a concept, so that knowledge bases may contain subsumption relations of the form “T(C ) is subsumed by P”, expressing that typical C-members have the property P. In order to perform nonmonotonic inferences, we define a “minimal model” semantics ALC + Tmin for ALC + T. The intuition is that preferred, or minimal models are those that maximise typical instances of concepts. By means of ALC + Tmin we are able to infer defeasible properties of (explicit or implicit) individuals. We also present a tableau calculus for deciding ALC + Tmin entailment. Main contributes of this paper have been also presented at the 11th European Conference on Logics in Artificial Intelligence "JELIA 2008".

Country
Italy
Related Organizations
Keywords

Description Logics; Nonmonotonic Reasoning

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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