Proceedings of the 7th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-2011) 2011
DOI: 10.2991/eusflat.2011.133
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A logic of the similarity with prototypes and its relationship to fuzzy logic

Abstract: Fuzzy sets are widely used to model vague properties. According to a common understanding, a fuzzy set represents the degrees of similarity of precisely specified objects with the prototypes of the considered vague property. We propose a logic based on this idea, using an entailment relation which was introduced in a work of Dubois, Prade, Esteva, Garcia, and Godo. The logic allows reasoning about the similarity with specific sets of prototypes; however, set-theoretic operations among the sets of prototypes as… Show more

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Cited by 2 publications
(2 citation statements)
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“…The closeness (or proximity) relation between the interpretations gives birth to a graded consequence relation, which is the basis for a logic of similarity dedicated to interpolation [37], and captures fuzzy logic-based approximate reasoning. In a similar spirit, a logic allowing to reason about the similarity with respect to specific sets of prototypes has been recently proposed [111].…”
Section: Similaritymentioning
confidence: 99%
“…The closeness (or proximity) relation between the interpretations gives birth to a graded consequence relation, which is the basis for a logic of similarity dedicated to interpolation [37], and captures fuzzy logic-based approximate reasoning. In a similar spirit, a logic allowing to reason about the similarity with respect to specific sets of prototypes has been recently proposed [111].…”
Section: Similaritymentioning
confidence: 99%
“…These metrics were incorporated into a multi-objective fitness function, the guiding criterion for evolutionary selection. In the paper [25] , the author discusses optimizing membership functions in a hierarchical Fuzzy Logic Controller for controlling a small autonomous parafoil used in reconnaissance and land survey missions. They manage the rule base size using a unique Combs method to prevent exponential rule expansion.…”
Section: Introductionmentioning
confidence: 99%