Connectionist Models of Social Reasoning and Social Behavior

by Stephen J. Read (Editor)

Although neural network models have had a dramatic impact on the cognitive and brain sciences, social psychology has remained largely unaffected by this intellectual explosion. The first to apply neural network models to social phenomena, this book includes chapters by nearly all of the individuals currently working in this area. Bringing these various approaches together in one place, it allows readers to appreciate the breadth of these approaches, as well as the theoretical commonality of many of these models.

The contributors address a number of central issues in social psychology and show how these kinds of models provide insight into many classic issues. Many chapters hint that this approach provides the seeds of a theoretical integration that the field has lacked. Each chapter discusses an explicit connectionist model of a central problem in social psychology. Since many of the contributors either use a standard architecture or provide a computer program, interested readers, with a little work, should be able to implement their own variations of models.

Chapters are devoted to the following topics and
* the learning and application of social categories and stereotypes;
* causal reasoning, social explanation, and person perception;
* personality and social behavior;
* classic dissonance phenomena; and
* belief change and the coherence of large scale belief systems.

396 pages, Paperback

First published May 1, 1998

About the author

Stephen J. Read is Professor of Psychology at the University of Southern
California, head of the social psychology area, and a Fellow of the Association
for Psychological Science and the Society for Experimental Social Psychology.
Dr. Read has edited three books and published over 100 journal articles and
book chapters on person perception, causal reasoning, attachment theory,
decision-making, use of interactive media (DVD and game) for changing risky
sexual behavior, personality, and the neurobiology of risky decision-making. He
has developed and published neural network models of person perception, causal
reasoning, cognitive dissonance, personality and motivation, and risky decisionmaking.
He has also worked on computational models of personality in intelligent
agents and models of the role of narrative representations in military decisionmaking.
Recently, he has focused on integrating work on the neurobiological
bases of risky decision-making with neural network models of the neural systems
involved in risky decision-making.