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Related Experiment Video

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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

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Published on: September 8, 2023

Quantum-like model of cognitive decision making and information processing.

Andrei Khrennikov¹

¹International Center for Mathematical Modeling in Physics and Cognitive Sciences, University of Växjö, Växjö, Sweden.

|November 18, 2008

Summary

This study introduces a quantum-like (QL) model for the Shafir-Tversky effect in cognitive psychology. It explains this effect as a result of mixing data from incompatible contexts, violating probability laws.

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Area of Science:

Cognitive Psychology
Quantum Cognition
Decision Theory

Background:

The Shafir-Tversky effect is a well-documented phenomenon in cognitive psychology.
This effect demonstrates deviations from rational choice theory under uncertainty.
Previous explanations have not fully captured the contextual nature of the observed biases.

Purpose of the Study:

To propose a quantum-like (QL) representation of the Shafir-Tversky effect.
To explain the effect as arising from the mixing of statistical data from incompatible contexts.
To introduce a quantitative measure for contextual incompatibility.

Main Methods:

Application of the contextual approach to cognitive decision-making.
Modeling contexts within the Prisoner's Dilemma (PD) using probability amplitudes (mental wave functions).
Analysis of experimental data using concepts of trigonometric and hyperbolic interference.

Main Results:

The Shafir-Tversky effect can be understood as a violation of the law of total probability due to mixed contexts.
A coefficient of interference is proposed to quantify contextual incompatibility.
Distinct interference patterns (trigonometric vs. hyperbolic) are identified in Shafir-Tversky experiments.

Conclusions:

QL theory provides a novel framework for understanding cognitive biases like the Shafir-Tversky effect.
Contextual incompatibility plays a crucial role in decision-making under uncertainty.
The study opens avenues for exploring QL decision-making, rationality, and ethics.