Exemplar-Based Random-Walk Model 1 An Exemplar-Based Random-Walk Model of Categorization and Recognition

Exemplar-Based Random-Walk Model 2 Abstract A fundamental issue in cognitive psychology and cognitive science concerns the manner in which people represent categories in memory and make decisions about category membership. In this chapter we provide a review of a process-oriented mathematical model of categorization known as the exemplar-based random-walk (EBRW) model (Nosofsky & Palmeri, 1997a). The EBRW model is a member of the class of exemplar models. According to such models, people represent categories by storing individual exemplars of the categories in memory, and classify objects on the basis of their similarity to the stored exemplars. The EBRW model combines ideas ranging from the fields of choice and similarity, to the development of automaticity, to response-time models of evidence accumulation and decision making. This integrated model explains relations between categorization and a wide variety of other fundamental cognitive processes, including individual-object identification, the development of expertise in tasks of skilled performance, and old-new recognition memory. Furthermore, it provides an account of how categorization and recognition decision making unfold through time. In addition to reviewing the EBRW model, we also provide comparisons with some other process models of categorization.