Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
  1. Home
  2. Search

Refine search

Refine search

Access:
Content type:
Publication date:
Apply   From and To filters
Subject: Show more
Journals Show more
Publishers: Show more
Societies Show more
Series: Show more
Collections: Show more

Actions for selected content:

Select all | Deselect all
  • View selected items
  • Export citations
  • Download PDF (zip)
  • Save to Kindle
  • Save to Dropbox
  • Save to Google Drive

Save Search

You can save your searches here and later view and run them again in "My saved searches".

Please provide a title, maximum of 40 characters.
Cancel
×

1 results

  • 23 - Computational Modeling of Visual Information Processing

  • from Part III - Computational Modeling of Various Cognitive Functionalities and Domains
  • Edited by Ron Sun
  • Book:
    The Cambridge Handbook of Computational Psychology
    Published online:
    05 June 2012
    Print publication:
    28 April 2008, pp 612-634

  • Summary

    The most frequently used computational models in social psychology are probably various kinds of connectionist models, such as constraint satisfaction networks, feedforward pattern associators with delta-rule learning, and multilayer recurrent networks with learning. The chapter begins with work on causal learning, causal reasoning, and impression formation. A large number of central phenomena in social psychology can be captured by a fairly simple feedback or recurrent network with learning. Important findings on causal learning, causal reasoning, individual and group impression formation, and attitude change can all be captured within the same basic architecture. This suggests that we might be close to being able to provide an integrated theory or account of a wide range of social psychological phenomena. It also suggests that underlying the apparent high degree of complexity of social and personality phenomena may be more fundamental simplicity.