On some typical values for Atanassov’s intuitionistic fuzzy sets

This paper is a continuation of our previous works on typicality in terms of Atanassovpsilas intuitionistic fuzzy sets (A-IFSs, for short)¹ We follow the line of reasoning known from psychological and cognitive sciences, in particular from linguistic experiments, and verify how those results work in classification - a typical problem in computer science, decision sciences, etc. We concentrate on a typical example in cognitive sciences: to which extent a linguistic representation in a psychological space (we start from nominal data - names are assigned to objects as labels) succeeds in predicting categories via A-IFSs. First, we consider a model of categories with a geometrical centroid model with the similarity defined in terms of a distance to centroids. Next, we verify if the extreme ideals, which are important in cognitive processes when categories are learnt in the presence of an alternative (contrast) category, give comparative results. Finally, we discuss if the ldquoreachable extreme idealsrdquo give comparative results. We show that A-IFSs make it possible to reflect a positive and negative information via the membership and non-membership degrees. Though the paper presents an ongoing research, the results obtained are promising and point out the usefulness and strength of A-IFSs as a tool to account for more aspects of vague data and information.