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Knowledge representation in fuzzy logicThe 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.
Document ID
19890064792
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Zadeh, Lotfi A.
(California, University Berkeley, United States)
Date Acquired
August 14, 2013
Publication Date
March 1, 1989
Publication Information
Publication: IEEE Transactions on Knowledge and Data Engineering
Volume: 1
ISSN: 1041-4347
Subject Category
Cybernetics
Accession Number
89A52163
Funding Number(s)
CONTRACT_GRANT: AF-AFOSR-89-0084
CONTRACT_GRANT: NCC2-275
Distribution Limits
Public
Copyright
Other

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