Prototypes in the mist: The early epochs of category learning.

Abstract

Recent ideas about category learning have favored exemplar processes over prototype processes. However, research has focused on small, poorly differentiated categories and on task-final performances—both may highlight exemplar strategies. Thus, we evaluated participants' categorization strategies and standard categorization models at successive stages in the learning of smaller, less differentiated categories and larger, more differentiated categories. In the former case, the exemplar model dominated even early in learning. In the latter case, the prototype model had a strong early advantage that gave way slowly. Alternative models, and even the behavior of individual parameters within models, suggest a psychological transition from prototype-based to exemplar-base d processing during category learning and show that different category structures produce different trajectories of learning through the larger space of strategies.