Decision boundaries in one-Dimensional categorization

Decision-boundary theories of categorization are often difficult to distinguish from exemplar-based theories of categorization. The authors developed a version of the decision-boundary theory, called the single-cutoff model, that can be distinguished from the exemplar theory. The authors present 2 experiments that test this decision-boundary model. The results of both experiments point strongly to the absence of single cutoffs in most participants, and no participant displayed use of the optimal boundary. The range of nonoptimal solutions shown by individual participants was accounted for by an exemplar-based adaptive-learning model. When combined with the results of previous research, this suggests that a comprehensive model of categorization must involve both rules and exemplars, and possibly other representations as well.