We describe PreDeLo 1.0, a theorem prover for preferential Description Logics (DLs). These are nonmonotonic extensions of standard DLs based on a typicality operatorT, which enjoys a preferential semantics. PreDeLo 1.0 is a Prolog implementation of labelled tableaux calculi for such extensions, and it is able to deal with the preferential extension of the basic DL ALC as well as with the preferential extension of the lightweight DL DL-Litecore . The Prolog implementation is inspired by the "lean" methodology, whose basic idea is that each axiom or rule of the tableaux calculi is implemented by a Prolog clause of the program. Concerning ALC, PreDeLo 1.0 considers two extensions based, respectively, on Kraus, Lehmann and Magidor's preferential and rational entailment. In this paper, we also introduce a tableaux calculus for checking entailment in the rational extension of ALC. © Springer International Publishing Switzerland 2013.

PreDeLo 1.0: a Theorem Prover for Preferential Description Logics

GLIOZZI, Valentina;POZZATO, GIAN LUCA
2013-01-01

Abstract

We describe PreDeLo 1.0, a theorem prover for preferential Description Logics (DLs). These are nonmonotonic extensions of standard DLs based on a typicality operatorT, which enjoys a preferential semantics. PreDeLo 1.0 is a Prolog implementation of labelled tableaux calculi for such extensions, and it is able to deal with the preferential extension of the basic DL ALC as well as with the preferential extension of the lightweight DL DL-Litecore . The Prolog implementation is inspired by the "lean" methodology, whose basic idea is that each axiom or rule of the tableaux calculi is implemented by a Prolog clause of the program. Concerning ALC, PreDeLo 1.0 considers two extensions based, respectively, on Kraus, Lehmann and Magidor's preferential and rational entailment. In this paper, we also introduce a tableaux calculus for checking entailment in the rational extension of ALC. © Springer International Publishing Switzerland 2013.
2013
AI*IA 2013 - XIIIth International Conference of the Italian Association for Artificial Intelligence
Torino
December 2013
Proceedings of AI*IA 2013
Springer
8249
60
72
978-331903523-9
https://link.springer.com/chapter/10.1007/978-3-319-03524-6_6
L. Giordano; V. Gliozzi; A. Jalal; N. Olivetti; G.L. Pozzato
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/139931
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