title: A neural network simulation of the outgroup homogeneity effect.
abstract: This article presents a neural network simulation of the out-group homogeneity effect (OHE). The model is a feedback network with delta-rule learning that has been previously used to simulate other aspects of stereotype learning, as well as causal learning and reasoning, and human memory. This simulation achieves 2 goals: First, we show that the model could successfully simulate the OHE. We argue that this is due to the error-correcting nature of delta-rule learning. Second, we show that each of 5 aspects of the simulation influences the size of the OHE: (a) the ratio of in-group to out-group size, (b) the overall population size, (c) the learning rate, (d) the decay rate for weights, and (e) increased learning for extreme cases. The psychological relevance of these parameters and ways to study them are presented. Advantages of the model in terms of breadth of coverage for studying social cognitive phenomena are discussed.
authors.affiliation: Department of Psychology, University of Southern California, Los Angeles, CA 90089-1061, USA. read@usc.edu.
authors.forename: Stephen J
authors.initials: SJ
authors.lastname: Read
authors.forename: Darren I
authors.initials: DI
authors.lastname: Urada
mesh_terms: D006126:Group Processes; D006127:Group Structure; D006801:Humans; D008432:Mathematical Computing; D016571:Neural Networks, Computer; D015203:Reproducibility of Results; D012933:Social Identification; D012938:Social Perception; D013240:Stereotyping