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On Operations of Restriction and Freezing on Monadic Fuzzy Quantifiers Over Fuzzy Domains

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Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2022)

Abstract

This article introduces important operations on the class of monadic fuzzy quantifiers, namely, restriction and freezing. These operations are introduced and investigated in the novel frame of monadic fuzzy quantifiers over fuzzy domains.

The second author announces a support of the ERDF/ESF project AI-Met4AI No. CZ.02.1.01/0.0/0.0/17_049/0008414.

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Notes

  1. 1.

    Note that a generalized quantifier is said to be monadic if its arguments are (fuzzy) sets, such as in “Most tigers cannot swim” (type \(\langle 1, 1\rangle \)). Here, the arguments of “most” are a set of tigers and a set of beings that can swim. More complicated are polyadic quantifiers, for which at least one of its arguments is a relation.

  2. 2.

    Note that \(P_{>5}\) is, in accordance with Definition 6, the relativization of \(Q_{>5}\), cf. Theorem 2.

  3. 3.

    More specifically, \((C_{M\cup N}\cup A_{M\cup N})\cap B_{M\cup N} = (C_{M\cup N}\cup A_{M\cup N})\cap (B_{M\cup N}\cap C_{M\cup N})\) does not hold in general; therefore, the fuzzy quantifier Q can assign different values for fuzzy sets \(B_{M\cup N}\) and \((B\cap C)_{M\cup N}\).

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Correspondence to Michal Holčapek .

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Dvořák, A., Holčapek, M. (2022). On Operations of Restriction and Freezing on Monadic Fuzzy Quantifiers Over Fuzzy Domains. In: Ciucci, D., et al. Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2022. Communications in Computer and Information Science, vol 1601. Springer, Cham. https://doi.org/10.1007/978-3-031-08971-8_56

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  • DOI: https://doi.org/10.1007/978-3-031-08971-8_56

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