Abstract
This paper provides an overview of some of the issues in using fuzzy sets for knowledge representation in computer systems. Since a fuzzy set is fully determined by its membership function the chief issues in fuzzy knowledge representation relate to how best to determine membership functions. A number of methods are discussed. However an alternative approach is to use type-2 fuzzy sets. Type-2 fuzzy sets allow for linguistic membership grades where the grades are themselves type-1 fuzzy sets. This paper explores two ways type-2 sets can represent knowledge and argues that type-2 fuzzy sets offer a powerful alternative to type-1 knowledge representation.
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