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Fuzzy concepts in an object oriented expert system shell
Author(s) -
Leung K. S.,
Wong M. H.
Publication year - 1992
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.4550070206
Subject(s) - computer science , vagueness , fuzzy logic , knowledge representation and reasoning , expert system , artificial intelligence , legal expert system , neuro fuzzy , representation (politics) , object (grammar) , fuzzy control system , politics , political science , law
Fuzzy logic is one of the methods to model the vagueness and imprecision of human knowledge. Some rule‐based expert system shells have been successfully developed and have demonstrated the power of fuzzy logic in dealing with inexact reasoning and rule inferences. However, using rules for knowledge representation is not structured enough. In addition, knowledge cannot be easily represented in an abstracted (hierarchical) from. In this article the introduction of fuzzy concepts into object oriented knowledge representation (OOKR), which is a structured knowledge representation scheme, is presented. A framework for handling all the possible fuzzy concepts in OOKR at both the dynamic and static levels is proposed. In order to handle the inheritance mechanism and to model the relations among classes, instances, and attributes, some new fuzzy concepts and operations are introduced. These concepts and operations are developed from the semantic meaning rather than by an ad hoc approach. A prototype of the expert system shell. System FX‐I, has been successfully developed based on the above framework, showing the feasibility of handling inexact knowledge in a structural way.