Quantum decision theory in simple risky choices

TL;DR

Quantum decision theory (QDT) applies quantum mechanics mathematics to model decision making under uncertainty, successfully predicting group behavior and offering a practical guide for analyzing binary lottery choices.

Contribution

This paper revisits QDT formalism, demonstrates its application to binary lotteries, and provides a practical guide for researchers in decision-making studies.

Findings

Group data aligns well with the quarter law prediction.

Individual data suggests potential for refining the quarter law.

QDT effectively models decision making in risky choices.

Abstract

Quantum decision theory (QDT) is a recently developed theory of decision making based on the mathematics of Hilbert spaces, a framework known in physics for its application to quantum mechanics. This framework formalizes the concept of uncertainty and other effects that are particularly manifest in cognitive processes, which makes it well suited for the study of decision making. QDT describes a decision maker's choice as a stochastic event occurring with a probability that is the sum of an objective utility factor and a subjective attraction factor. QDT offers a prediction for the average effect of subjectivity on decision makers, the quarter law. We examine individual and aggregated (group) data, and find that the results are in good agreement with the quarter law at the level of groups. At the individual level, it appears that the quarter law could be refined in order to reflect individual characteristics. This article revisits the formalism of QDT along a concrete example and offers a practical guide to researchers who are interested in applying QDT to a dataset of binary lotteries in the domain of gains.