Automata-based Reasoning in Fuzzy Description Logics
نویسنده
چکیده
Description logics (DLs) are a family of well-studied knowledge representation formalisms designed to express and reason with the conceptual knowledge of application domains in a clear and well-understood manner. They have been successfully applied for representing large application domains, most prominently from the biological and medical fields. In their classical form, DLs are not adequate for handling vague or imprecise knowledge, which is a common staple in bio-medical knowlege. To alleviate this problem, fuzzy extensions of DLs have been introduced. As a prototypical example, we consider here the smallest propositionally closed fuzzy DL, which we call ⊗-ALC. The fuzzy DL ⊗-ALC is based on concepts and roles, which are interpreted as (fuzzy) unary and binary relations, respectively. Given the disjoint sets NR, and NC of role, and concept names, respectively, ⊗-ALC concepts are built through the grammar rule
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Reasoning in Fuzzy Description Logics using Automata
Automata-based methods have been successfully employed to prove tight complexity bounds for reasoning in many classical logics, and in particular in Description Logics (DLs). Very recently, the ideas behind these automata-based approaches were adapted for reasoning also in fuzzy extensions of DLs, with semantics based either on finitely many truth degrees or the Gödel t-norm over the interval [...
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[2] Karsten Lehmann and Rafael Peñaloza. The complexity of computing the behaviour of lattice automata on infinite trees. On the decidability status of fuzzy ALC with general concept inclusions. [4] Stefan Borgwardt and Rafael Peñaloza. Consistency reasoning in lattice-based fuzzy description logics. Context-dependent views to axioms and consequences of semantic web ontologies. Classifying soft...
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