Distributivity of fuzzy implications over different fuzzy logic connectives have a very important role to play in efficient inferencing in approximate reasoning, especially in fuzzy control systems (see \cite{Combs_Andrews_1998,Jayaram2008} and \cite{Baczynski_Jayaram_2008}). Recently in some considerations connected with these distributivity laws, the following functional equation appeared (see \cite{Baczynski_Jayaram_2009})
f(min(x+y,a))=min(f(x)+f(y),b),
where a,b>0 and f:[0,a]→[0,b] is an unknown function. In this paper we consider in detail a generalized version of this equation, namely the equation
f(m1(x+y))=m2(f(x)+f(y)),
where m1,m2 are functions defined on some intervals of \R satisfying additional assumptions. We analyze the cases when m2 is injective and when m2 is not injective.
Several open problems posed during FSTA 2006 (Liptovský Ján, Slovakia) are presented. These problems concern the classification of strict triangular norms, Lipschitz t-norms, interval semigroups, copulas, semicopulas and quasi-copulas, fuzzy implications, means, fuzzy relations, MV-algebras and effect algebras.
The core of the expert knowledge is typically represented by a set of rules (implications) assigned with weights specifying their (un)certainties. In the paper, a method for hierarchical selection and correction of expert's weighted rules is described particularly in the case when Łukasiewicz's fuzzy logic with evaluated syntax for dealing with weights is used.
In this paper, we introduce the product, coproduct, equalizer and coequalizer notions on the category of fuzzy implications on a bounded lattice that results in the existence of the limit, pullback, colimit and pushout. Also isomorphism, monic and epic are introduced in this category. Then a subcategory of this category, called the skeleton, is studied. Where none of any two fuzzy implications are Φ-conjugate.