Flexible planning using fuzzy description logics: Theory and application

Authors:
Lian Shi;Jigui Sun;Shuai Lu;Minghao Yin
Affiliations:
College of Computer Science, Jilin University, Changchun 130012, China and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Changchun 130012, China;College of Computer Science, Jilin University, Changchun 130012, China and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Changchun 130012, China;College of Computer Science, Jilin University, Changchun 130012, China and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Changchun 130012, China;College of Computer Science, Northeast Normal University, 130024, China
Venue:
Applied Soft Computing
Year:
2009

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Abstract

Description logics (DLs for short) are formalisms for representing knowledge of various domains in a structured and formally well-understood way. Typically, DLs are limited to deal with precise and well-defined concepts. In this paper we first present a fuzzy extension of ALC*, called fuzzy ALC*, combining Zadeh's fuzzy logic with an expressive DL and define its syntax and semantics. Then we devote to taking advantage of the expressive power and reasoning capabilities of fuzzy ALC* by encoding flexible planning problems within the framework of fuzzy ALC*. Both theory and experimental results have shown that our method is sound and efficient.