Mathematical Fuzzy Logics [51, 60] have a long tradition with roots going back to the many-valued logics of Łukasiewicz, Gödel, and Kleene [57, 68, 73] and the Fuzzy Set Theory of Zadeh [111]. Their purpose is to model vagueness or imprecision in the real world, by introducing new degrees of truth as additional shades of gray between the Boolean true and false. For example, one can express the distinction between a person x having a high fever or a low fever as the degree of truth of the logical statement Fever (x). One of the central properties of fuzzy logics is truth functionality—the truth degree of a complex logical formula is uniquely determined by the truth degrees of its subformulas. This is a fundamental difference to other quantitative logics like probabilistic or possibilistic logics [56, 83].

Borgwardt, S., Peñaloza, R. (2017). Fuzzy description logics – A survey. In Proceedings of the 11th International Conference on Scalable Uncertainty Management (SUM 2017) (pp.31-45). Springer Verlag [10.1007/978-3-319-67582-4_3].

Fuzzy description logics – A survey

Peñaloza, R
2017

Abstract

Mathematical Fuzzy Logics [51, 60] have a long tradition with roots going back to the many-valued logics of Łukasiewicz, Gödel, and Kleene [57, 68, 73] and the Fuzzy Set Theory of Zadeh [111]. Their purpose is to model vagueness or imprecision in the real world, by introducing new degrees of truth as additional shades of gray between the Boolean true and false. For example, one can express the distinction between a person x having a high fever or a low fever as the degree of truth of the logical statement Fever (x). One of the central properties of fuzzy logics is truth functionality—the truth degree of a complex logical formula is uniquely determined by the truth degrees of its subformulas. This is a fundamental difference to other quantitative logics like probabilistic or possibilistic logics [56, 83].
paper
fuzzy logic, description logics
English
International Conference on Scalable Uncertainty Management (SUM 2017)
2017
Moral, S; Pivert, O; Sánchez, D; Marín, N
Proceedings of the 11th International Conference on Scalable Uncertainty Management (SUM 2017)
9783319675817
2017
10564
31
45
open
Borgwardt, S., Peñaloza, R. (2017). Fuzzy description logics – A survey. In Proceedings of the 11th International Conference on Scalable Uncertainty Management (SUM 2017) (pp.31-45). Springer Verlag [10.1007/978-3-319-67582-4_3].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/257251
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