title: ALCOVE: an exemplar-based connectionist model of category learning.
abstract: ALCOVE (attention learning covering map) is a connectionist model of category learning that incorporates an exemplar-based representation (Medin & Schaffer, 1978; Nosofsky, 1986) with error-driven learning (Gluck & Bower, 1988; Rumelhart, Hinton, & Williams, 1986). Alcove selectively attends to relevant stimulus dimensions, is sensitive to correlated dimensions, can account for a form of base-rate neglect, does not suffer catastrophic forgetting, and can exhibit 3-stage (U-shaped) learning of high-frequency exceptions to rules, whereas such effects are not easily accounted for by models using other combinations of representation and learning method.
authors.affiliation: Department of Psychology, Indiana University, Bloomington 47405.
authors.forename: J K
authors.initials: JK
authors.lastname: Kruschke
mesh_terms: D001288:Attention; D004193:Discrimination Learning; D005793:Generalization, Psychological; D006801:Humans; D011939:Mental Recall; D008960:Models, Psychological; D016571:Neural Networks, Computer; D010364:Pattern Recognition, Visual; D012054:Reinforcement, Psychology