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A model of transitive choice

M R Harris1, B O McGonigle

  • 1University of Edinburgh, U.K.

The Quarterly Journal of Experimental Psychology. B, Comparative and Physiological Psychology
|August 1, 1994
PubMed
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This study models transitive inference in squirrel monkeys using a rule-based system. The model successfully explains choice and reaction time data, suggesting item prominence, not just distance, influences decisions.

Area of Science:

  • Cognitive Science
  • Animal Behavior
  • Computational Neuroscience

Background:

  • Transitive inference is a complex cognitive process involving ordering relationships.
  • Previous studies on squirrel monkeys (McGonigle & Chalmers, 1977, 1992) provided rich data on learning and decision-making.
  • Observed phenomena include transitive choice, task transfer, and Symbolic Distance Effect (SDE).

Purpose of the Study:

  • To develop a formal, rule-based model of transitive inference.
  • To explain choice and reaction-time data from squirrel monkey experiments.
  • To investigate the factors influencing decision times in transitive inference tasks.

Main Methods:

  • Utilized a rule-based (production) system to model behavior.
  • Developed group-level and individual-level rule stacks.

Related Experiment Videos

  • Applied the model to data from McGonigle & Chalmers (1977, 1992) studies.
  • Analyzed decision-time data to assess reaction time variations.

    • Main Results:

    • The model successfully accounted for transitive choice and task transfer phenomena.
    • Small adjustments to the rule search procedure allowed the model to fit all observed data.
    • Decision time analysis indicated item prominence in the rule stack is a key factor, rather than solely interitem distance.
    • The model aligns with independent findings on reaction time variation.

    Conclusions:

    • A rule-based model can effectively capture transitive inference in squirrel monkeys.
    • Item prominence within a decision-making hierarchy significantly impacts reaction times.
    • The model provides a computational framework for understanding complex decision-making processes in non-human primates.