Abstract
Because people do not seem to use hard-edged categories in everyday thought, fuzzy set theory has some intuitively appealing formalisms which appear suitable for modelling natural cognitive schema. This paper presents tools for applying fuzzy set concepts to the social and behavioral sciences, and examples of their uses. The following issues are addressed: (1) Definitions of fuzziness and its measurement; (2) The measurement of intercategory overlap or synonymy; (3) Fuzzy set inclusion and overlap as the basis for a new hierarchical clustering method; and (4) Fuzzy set union and intersection as the basis for regional-interpretive models in multidimensional scaling and fuzzy taxonomies. Most of the examples for this paper are taken from empirical research into individuals' cognitive representations of helping behavior.
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