Abstract
A random set semantics for fuzzy labels is proposed in which we model the vagueness of fuzzy concepts in terms of their level of appropriateness as descriptions for values. This random set model is then shown to be characterised by a certain axiom system for appropriateness measures. It is then shown how some t-norms can generate appropriateness measures and an attempt is made to identify a family of t-norms that can be used consistently for this purpose. The calculus that is introduced is functional but not truth-functional.
Cite
CITATION STYLE
Lawry, J., & Recasens, J. (2003). A random set model for fuzzy labels. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 2711, pp. 357–369). Springer Verlag. https://doi.org/10.1007/978-3-540-45062-7_29
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