Abstract
Linguistic approximation is a well known problem in fuzzy set theory to describe an arbitrary fuzzy set in the most appropriate linguistic terms. It involves a search through the space of linguistic descriptions (labels) generated according to a given grammar and vocabulary. The vocabulary and grammar specify a language structure, i.e. allowable and meaningful combinations of primary linguistic terms, linguistic modifiers and linguistic connectives as well as the order of their composition. This structure may become quite complex when a larger vocabulary and more complicated grammatical rules are considered. Therefore linguistic approximation may require search techniques that are able to deal effectively with more complex linguistic structures. The paper presents an approach to linguistic approximation based on an evolutionary search technique, genetic programming. The approach is demonstrated with the results of the initial experiments.
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Kowalczyk, R. (1998). On linguistic approximation with genetic programming. In: Mira, J., del Pobil, A.P., Ali, M. (eds) Methodology and Tools in Knowledge-Based Systems. IEA/AIE 1998. Lecture Notes in Computer Science, vol 1415. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-64582-9_749
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DOI: https://doi.org/10.1007/3-540-64582-9_749
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