Speeded classification in a probabilistic category structure: contrasting exemplar-retrieval, decision-boundary, and prototype models.
Speeded perceptual classification experiments were conducted to distinguish among the predictions of exemplar-retrieval, decision-boundary, and prototype models. The key manipulation was that across conditions, individual stimuli received either probabilistic or deterministic category feedback. Regardless of the probabilistic feedback, however, an ideal observer would always classify the stimuli by using an identical linear decision boundary. Subjects classified the probabilistic stimuli with lower accuracy and longer response times than they classified the deterministic stimuli. These results are in accord with the predictions of the exemplar model and challenge the predictions of the prototype and decision-boundary models.
Department of Psychology, Indiana University Bloomington, Bloomington, IN 47405, USA. nosofsky@indiana.edu
Robert M
RM
Nosofsky
Roger D
RD
Stanton
D000704:Analysis of Variance; D002965:Classification; D003657:Decision Making; D006801:Humans; D008568:Memory; D008960:Models, Psychological; D011336:Probability; D011930:Reaction Time; D014796:Visual Perception