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Integrating Categorization and Decision-Making.

Rong Zheng1, Jerome R Busemeyer1, Robert M Nosofsky1

  • 1Department of Psychological and Brain Science, Indiana University.

Cognitive Science
|January 19, 2023
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Summary
This summary is machine-generated.

This study explored how categorization influences decisions in a two-stage task. A quantum cognition model better explained the observed empirical interference effects than an exemplar model.

Keywords:
Categorization-decisionExemplar modelInterference effectModel comparisonQuantum cognition model

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Area of Science:

  • Cognitive Science
  • Decision Making
  • Quantum Cognition

Background:

  • Individual categorization and decision processes are well-studied but their interaction in sequential tasks is less understood.
  • Previous research has not fully explored the interplay between categorization and decision-making within a unified framework.

Purpose of the Study:

  • To investigate the interaction between categorization and decision-making in a two-stage task.
  • To examine how probabilistic contingencies influence behavior in categorization-decision tasks.
  • To compare the explanatory power of a quantum cognition model versus a two-stage exemplar categorization model.

Main Methods:

  • Conducted two experiments involving a categorization-decision task with faces varying in width.
  • Manipulated probabilistic contingencies between stimuli, category assignments, and decision consequences across three groups.
  • Collected data on category responses, feedback, decision responses, and feedback across different sequences.

Main Results:

  • Participants showed only partial responsiveness to manipulated contingencies.
  • Evidence for empirical interference effects of categorization on decisions was observed.
  • A quantum cognition model provided a better fit to the data than a two-stage exemplar categorization model.

Conclusions:

  • Categorization significantly impacts subsequent decision-making, leading to empirical interference effects.
  • Quantum cognition principles, including superposition and entanglement, offer a robust explanation for these interference effects.
  • The quantum model demonstrates superior predictive accuracy for complex categorization-decision interactions.