ABSTRACT
According to exemplar models, learning involves the storage of instances in memory. Exemplar models do not assume that learning involves the computation of summary representations for categories or other groups of stimuli (as presumed in prototype models or rule-based models). Instead, it is assumed that each encounter with a stimulus leaves a separate trace in memory, and that subsequent categorisation, identification, or recognition depends on the retrieval of these specific memory traces. There are usually no constraints on the kind of information that can be contained in a memory trace. Exemplar information can be perceptual (referring to structural or surface properties of the object; Humphreys, Riddoch, & Quinlan, 1988) or semantic (referring to aspects of its meaning).
