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A Neural Network Simulation of the Outgroup Homogeneity Effect

Darren I. Urada

Department of Psychology, University of Southern California

This article presents a neural network simulation of the out-grouphomogeneity effect (OHE). The model is a feedback network with delta-rule learning that has been previouslv 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 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.

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