Abstract
Description Logics (DLs) are appropriate, widely used, logics for managing structured knowledge. They allow reasoning about individuals and concepts, i.e. set of individuals with common properties. Typically, DLs are limited to dealing with crisp, well defined concepts. That is, concepts for which the problem whether an individual is an instance of it is a yes/no question. More often than not, the concepts encountered in the real world do not have a precisely defined criteria of membership: we may say that an individual is an instance of a concept only to a certain degree, depending on the individual's properties. The DLs that deal with such fuzzy concepts are called fuzzy DLs. In order to deal with fuzzy, incomplete, indeterminate and inconsistent concepts, we need to extend the capabilities of fuzzy DLs further. In this paper, we will present an extension of fuzzy [Formula: see text], combining Smarandache's neutrosophic logic with a classical DL. In particular, concepts become neutrosophic (here neutrosophic means fuzzy, incomplete, indeterminate and inconsistent), thus, reasoning about such neutrosophic concepts is supported. We will define its syntax, its semantics, describe its properties and present a constraint propagation calculus for reasoning.
Highlights
The modelling and reasoning with uncertainty and imprecision is an important research topic in the Artificial Intelligence community
Description Logics (DLs) are a logical reconstruction of the so-called framebased knowledge representation languages, with the aim of providing a simple wellestablished Tarski-style declarative semantics to capture the meaning of the most popular features of structured representation of knowledge
A main point is that DLs are considered as to be attractive logics in knowledge based applications as they are a good compromise between expressive power and computational complexity
Summary
Haibin Wang Biostatistics Research and Informatics Core, Winship Cancer Institute. Andre Rogatko Biostatistics Research and Informatics Core, Winship Cancer Institute. Description Logics (DLs) are appropriate, widely used, logics for managing structured knowledge. They allow reasoning about individuals and concepts, i.e. set of individuals with common properties. The concepts encountered in the real world do not have a precisely defined criteria of membership: we may say that an individual is an instance of a concept only to a certain degree, depending on the individual’s properties. Concepts become neutrosophic (here neutrosophic means fuzzy, incomplete, indeterminate and inconsistent), reasoning about such neutrosophic concepts is supported. We will define its syntax, its semantics, describe its properties and present a constraint propagation calculus for reasoning in it
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