Decision processes in verifying category membership statements: Implications for models of semantic memory

Current models of semantic memory assume that natural categories are well-defined. Specific predictions of two such models, the Smith, Shoben, and Rips (1974a) two-stage feature comparison model and the Glass and Holyoak (1974/75) ordered search model, were tested and disconfirmed in Experiment I. We propose an alternative model postulating fuzzy categories represented as sets of characteristic properties. This model, combined with a Bayesian decision process, accounts for the results of three additional experiments, as well as for the major findings in the semantic memory literature. We argue that people verify category membership statements by assessing similarity relations between concepts rather than by using information which logically specifies the truth value of the sentence. Our data also imply that natural categories are fuzzy rather than well-defined.