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Associative Learning and Conditioning TheoryHuman and Non-Human Applications$
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Todd R. Schachtman and Steve S. Reilly

Print publication date: 2011

Print ISBN-13: 9780199735969

Published to Oxford Scholarship Online: May 2011

DOI: 10.1093/acprof:oso/9780199735969.001.0001

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Social Learning and Connectionism

Social Learning and Connectionism

Chapter:
(p.345) Chapter 16 Social Learning and Connectionism
Source:
Associative Learning and Conditioning Theory
Author(s):

Frank Van Overwalle

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780199735969.003.0104

This chapter reviews evidence to demonstrate that many judgments and biases in social cognition can be understood from a connectionist perspective. A basic feature of connectionist modelling is that many social judgments are driven by basic associative learning processes, most often by an error-minimizing algorithm as illustrated in the delta learning algorithm. Two major emergent properties falling naturally out from this learning algorithm are acquisition (sample size effects) and competition (discounting and augmentation). These properties are unique to error minimizing algorithms like delta learning. Empirical evidence is reviewed showing that causal en dispositional attributions are strongly determined by these emergent properties. In addition, a number of simulations are reviewed to illustrate that many other social judgments and biases might result from such connectionist learning processes. These simulations include person impression formation, assimilation and contrast, illusory correlations in groups, subtyping of extreme dissidents, cognitive dissonance, attitude formation through persuasive communication, and recent findings of brain imaging research on person perception. The common theme in this chapter is that a single connectionist learning mechanism—the delta algorithm—is capable of producing emerging properties that explain a rich set of empirical data in social cognition.

Keywords:   social connectionism, connectionist simulations, impression formation, group biases, attitude formation, social neuroscience

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