Lawrence Erlbaum Associates, Inc. A Neural Network Simulation of the Outgroup Homogeneity Effect

This article presents a neural network simulation ofthe out-group homogeneity effect (OHE). The model is a feedback network with delta-rule learning that has been previ-ouslv used to simulate other aspects o / stereot pe learning, a.s well as causal learning and reasoning, and human memory This simulation achieves 2 goals: First, we show that the model could successfsUlv simulate the OHE. We argue that this is due to the error-correcting nature ofdelta-rule learning. Second. we show that each of aspects of the simulation influences the size of the OHE: (a) the ratio ofin-group to out-group size, (b) the overall population size, (c) the learning rate, (d) the decay rate for weights, and (e) increased learningfor extreme cases. The psychological relevance of these parameters and ways to study them are presented. Advantages of the model in terms ofbreadth ofcoverage for studying social cognitive phenomena are discussed. The tendency to perceive out-group members as relatively similar to one another and in-group mem-bers as relatively more heterogeneous or dissimilar is known as the out-group homogeneity effect (OHE). This tendency to perceive out-group members as "all the same " is argued to increase stereotyping (Judd