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Reasoning with Very Expressive Fuzzy Description Logics
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| Venue: | JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH |
| Citations: | 52 - 21 self |
BibTeX
@MISC{Stoilos_reasoningwith,
author = {Giorgos Stoilos and Giorgos Stamou and Jeff Z. Pan and Vassilis Tzouvaras and Ian Horrocks},
title = { Reasoning with Very Expressive Fuzzy Description Logics},
year = {}
}
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Abstract
It is widely recognized today that the management of imprecision and vagueness will yield more intelligent and realistic knowledge-based applications. Description Logics (DLs) are a family of knowledge representation languages that have gained considerable attention the last decade, mainly due to their decidability and the existence of empirically high performance of reasoning algorithms. In this paper, we extend the well known fuzzy ALC DL to the fuzzy SHIN DL, which extends the fuzzy ALC DL with transitive role axioms (S), inverse roles (I), role hierarchies (H) and number restrictions (N). We illustrate why transitive role axioms are difficult to handle in the presence of fuzzy interpretations and how to handle them properly. Then we extend these results by adding role hierarchies and finally number restrictions. The main contributions of the paper are the decidability proof of the fuzzy DL languages fuzzy-SI and fuzzy-SHIN, as well as decision procedures for the knowledge base satisfiability problem of the fuzzy-SI and fuzzy-SHIN.
Keyphrases
expressive fuzzy description logic artificial intelligence research transitive role axiom fuzzy alc dl role hierarchy number restriction decision procedure high performance inverse role fuzzy shin dl fuzzy interpretation decidability proof fuzzy dl last decade description logic knowledge base satisfiability problem considerable attention knowledge representation realistic knowledge-based application main contribution
