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Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

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Published on: June 8, 2018

Quantum probability and conceptual combination in conjunctions.

James A Hampton1

  • 1Department of Psychology, City University London, City University, Northampton Square, London EC1V OHB, United Kingdom. Hampton@city.ac.uk

The Behavioral and Brain Sciences
|May 16, 2013
PubMed
Summary
This summary is machine-generated.

Quantum probability (QP) offers a new lens for category conjunctions, but struggles with the "guppy effect." This phenomenon, where a category fits a conjunction better than its components, challenges current quantum models of decision-making.

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Area of Science:

  • Cognitive Science
  • Decision Making
  • Quantum Cognition

Background:

  • The conjunction fallacy describes the tendency to judge a conjunction of events as more probable than one of its constituents.
  • Pothos & Busemeyer's quantum probability (QP) account offers a novel framework for understanding cognitive phenomena, including the conjunction fallacy.

Purpose of the Study:

  • To evaluate the capacity of the Pothos & Busemeyer (P&B) quantum probability (QP) account to explain category conjunctions.
  • To investigate whether the P&B QP account can adequately model the "guppy effect" in category conjunctions.

Main Methods:

  • Theoretical analysis of the Pothos & Busemeyer (P&B) quantum probability (QP) framework.
  • Examination of the "guppy effect" within the context of category conjunctions and its implications for existing QP models.

Main Results:

  • The P&B quantum probability (QP) account, as currently formulated, does not fully capture the nuances of category conjunctions.
  • Specifically, the model fails to account for the "guppy effect," where a category is a better fit for a conjunction (A^B) than for its individual components (A or B).

Conclusions:

  • The P&B quantum probability (QP) account requires refinement to encompass all observed phenomena in category conjunctions, including the "guppy effect."
  • Further development of quantum cognitive models is necessary to fully explain complex human judgments in categorization and probability.