Connectionist Models of Social Reasoning and Social Behavior

Connectionist Models of Social Reasoning and Social Behavior

Connectionist Models of Social Reasoning and Social Behavior

Connectionist Models of Social Reasoning and Social Behavior

Synopsis

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 models:

• 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.

Excerpt

Neural network models, also called connectionist or parallel distributed processing models, seem to represent a major paradigm shift in cognitive psychology, cognitive science, and artificial intelligence. Such models move us away from the idea of mind as computer, and instead promise the possibility of brain style models of the mind, admitting the possibility that models of high level cognitive processing can be built from simple neuron- like units. That is, we can build computational models of the mind composed of units functionally similar to the physical units that compose a real brain. This approach has led to some fundamental new insights about the way the mind might work and the way it might interact with the environment.

Surprisingly, given the importance of these models, until recently social psychologists had paid little attention to them. Yet, these models directly address several fundamental characteristics of social perception and social interaction: the simultaneous integration of multiple pieces of information and the quite short time frame within which such integration occurs. Any mundane act of social perception (and any resulting behavior) results from the simultaneous integration of multiple pieces of information, such that the meaning of each piece of information mutually influences and constrains the meaning of each other piece. Thus, social perception can be viewed as the solution of simultaneous mutually interacting constraints. Moreover, this integration typically takes place in a very short time frame, much shorter than would be possible for any kind of reasonable serial integration process. Thus, much of social perception must occur in parallel. Both of . . .

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