DocumentCode :
920564
Title :
Knowledge representation in fuzzy logic
Author :
Zedeh, L.A.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley, CA
Volume :
1
Issue :
1
fYear :
1989
fDate :
3/1/1989 12:00:00 AM
Firstpage :
89
Lastpage :
100
Abstract :
The author presents a summary of the basic concepts and techniques underlying the application of fuzzy logic to knowledge representation. He then describes a number of examples relating to its use as a computational system for dealing with uncertainty and imprecision in the context of knowledge, meaning, and inference. It is noted that one of the basic aims of fuzzy logic is to provide a computational framework for knowledge representation and inference in an environment of uncertainty and imprecision. In such environments, fuzzy logic is effective when the solutions need not be precise and/or it is acceptable for a conclusion to have a dispositional rather than categorical validity. The importance of fuzzy logic derives from the fact that there are many real-world applications which fit these conditions, especially in the realm of knowledge-based systems for decision-making and control
Keywords :
fuzzy logic; knowledge representation; computational system; control; decision-making; fuzzy logic; imprecision; inference; knowledge representation; knowledge-based systems; meaning; real-world applications; uncertainty; Artificial intelligence; Calculus; Computer science; Fuzzy logic; Humans; Intelligent networks; Knowledge representation; Logic testing; Uncertainty; Unemployment;
fLanguage :
English
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1041-4347
Type :
jour
DOI :
10.1109/69.43406
Filename :
43406
Link To Document :
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