Categories of fuzzy-type automata with Kleisli morphisms

IF 2.7 1区 数学 Q2 COMPUTER SCIENCE, THEORY & METHODS Fuzzy Sets and Systems Pub Date : 2025-03-13 DOI:10.1016/j.fss.2025.109366
Jiří Močkoř
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Abstract

We introduce the categories of monadic automata, where morphisms between automata are relations defined by monads, that is, morphisms in the Kleisli categories. We show that many standard categories of automata including deterministic, non-deterministic, or fuzzy automata with relations as morphisms are special examples of this category. We also show that there is a strong relation among functors between the Kleisli categories, on the one hand, and functors between these categories of monadic automata, on the other. We extend the definition of a language accepted by a monadic automata with Kleisli morphisms and investigate relationships between categories of these languages and Kleisli categories.
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具有Kleisli态射的模糊自动机的范畴
引入一元自动机的范畴,其中自动机之间的态射是由一元定义的关系,即Kleisli范畴中的态射。我们证明了许多自动机的标准类别,包括确定性、非确定性或模糊自动机的关系作为态射是这一类的特殊例子。我们还证明了一方面Kleisli范畴之间的函子与另一方面一元自动机这些范畴之间的函子之间有很强的关系。我们扩展了具有Kleisli态的一元自动机所接受的语言的定义,并研究了这些语言的范畴与Kleisli范畴之间的关系。
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来源期刊
Fuzzy Sets and Systems
Fuzzy Sets and Systems 数学-计算机:理论方法
CiteScore
6.50
自引率
17.90%
发文量
321
审稿时长
6.1 months
期刊介绍: Since its launching in 1978, the journal Fuzzy Sets and Systems has been devoted to the international advancement of the theory and application of fuzzy sets and systems. The theory of fuzzy sets now encompasses a well organized corpus of basic notions including (and not restricted to) aggregation operations, a generalized theory of relations, specific measures of information content, a calculus of fuzzy numbers. Fuzzy sets are also the cornerstone of a non-additive uncertainty theory, namely possibility theory, and of a versatile tool for both linguistic and numerical modeling: fuzzy rule-based systems. Numerous works now combine fuzzy concepts with other scientific disciplines as well as modern technologies. In mathematics fuzzy sets have triggered new research topics in connection with category theory, topology, algebra, analysis. Fuzzy sets are also part of a recent trend in the study of generalized measures and integrals, and are combined with statistical methods. Furthermore, fuzzy sets have strong logical underpinnings in the tradition of many-valued logics.
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