To test preschoolers’ ability to flexibly switch between abstract rules differing in difficulty, nintythree 3-, 4-, and 5-year-olds were instructed to switch from an (easier) shape-sorting to a (harder) function-sorting rule, or vice versa. Children learned one rule, sorted four test sets, then learned the other rule, and sorted four more sets. In a control condition, seventy-two 3–5-year-old c...

Fuzzy Sets and Systems 161 (2010) 412-432 Elsevier www.elsevier.com/locate/fss A Categorical Semantics for Fuzzy Predicate Logic

does not satisfy (EP), because for x = 0.3, y = 0.5 and z = 0.5 we get I (x, I (y, z)) = 0.7 = 0.5 = I (y, I (x, z)). The corrected last two rows are provided in Table 1 here. In both of these cases the natural negation NI is the classical negation NC(x) = 1 − x. One can easily check that the first function satisfies (I1) and it does not satisfy (EP), because for x = 0.3, y = 1 and z = 0, we ge...

In this work we solve an open problem of U.Höhle [Problem 11, Fuzzy Sets and Systems 145 (2004) 471-479]. We show that the solution gives a characterization of all conditionally cancellative t-subnorms. Further, we give an equivalence condition for a conditionally cancellativite t-subnorm to be a t-norm and hence show that conditionally cancellativite t-subnorms whose natural negations are stro...

In this chapter, we discuss the application of evolutionary multiobjective optimization (EMO) to association rule mining. Especially, we focus our attention on classification rule mining in a continuous feature space where the antecedent and consequent parts of each rule are an interval vector and a class label, respectively. First we explain evolutionary multiobjective classification rule mini...