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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John, R. (2000). Fuzzy Sets and Knowledge Representation. In: Szczepaniak, P.S., Lisboa, P.J.G., Kacprzyk, J. (eds) Fuzzy Systems in Medicine. Studies in Fuzziness and Soft Computing, vol 41. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1859-8_4
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DOI: https://doi.org/10.1007/978-3-7908-1859-8_4
Publisher Name: Physica, Heidelberg
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