How to approximate fuzzy sets: mind-changes and the Ershov Hierarchy.

Computability theorists have introduced multiple hierarchies to measure the complexity of sets of natural numbers. The Kleene Hierarchy classifies sets according to the first-order complexity of their defining formulas. The Ershov Hierarchy classifies limit computable sets with respect to the number...

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Detalles Bibliográficos
Publicado en:Synthese Vol. 201; no. 2; pp. 1 - 26
Autores principales: Bazhenov, Nikolay, Mustafa, Manat, Ospichev, Sergei, San Mauro, Luca
Formato: Artículo
Publicado: Springer Nature Feb2023
Acceso en línea:Ver este registro en EBSCOhost
Descripción
Sumario:Computability theorists have introduced multiple hierarchies to measure the complexity of sets of natural numbers. The Kleene Hierarchy classifies sets according to the first-order complexity of their defining formulas. The Ershov Hierarchy classifies limit computable sets with respect to the number of mistakes that are needed to approximate them. Biacino and Gerla extended the Kleene Hierarchy to the realm of fuzzy sets, whose membership functions range in a complete lattice. In this paper, we combine the Ershov Hierarchy and fuzzy set theory, by introducing and investigating the Fuzzy Ershov Hierarchy.