Information integration in multiple cue judgment: a division of labor hypothesis

Cognition. 2008 Jan;106(1):259-98. doi: 10.1016/j.cognition.2007.02.003. Epub 2007 Mar 21.

Abstract

There is considerable evidence that judgment is constrained to additive integration of information. The authors propose an explanation of why serial and additive cognitive integration can produce accurate multiple cue judgment both in additive and non-additive environments in terms of an adaptive division of labor between multiple representations. It is hypothesized that, whereas the additive, independent linear effect of each cue can be explicitly abstracted and integrated by a serial, additive judgment process, a variety of sophisticated task properties, like non-additive cue combination, non-linear relations, and inter-cue correlation, are carried implicitly by exemplar memory. Three experiments investigating the effect of additive versus non-additive cue combination verify the predicted shift in cognitive representations as a function of the underlying combination rule.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Association Learning*
  • Attention*
  • Cues*
  • Discrimination Learning
  • Female
  • Generalization, Psychological
  • Humans
  • Judgment*
  • Male
  • Models, Theoretical
  • Probability Learning*
  • Problem Solving
  • Serial Learning*