Quantitative Predictions in Quantum Decision Theory

Yukalov, V. I.; Sornette, Didier

doi:10.1109/tsmc.2016.2596578

Cited by 51 publications

(71 citation statements)

References 73 publications

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“…Typical values of the attraction factors are derived by Yukalov and Sornette (2016) in the general case of a decision involving more than two prospects.…”

Section: Quarter Law: Prediction Of Qdt On Attraction Factorsmentioning

confidence: 99%

Quantum Decision Theory in Simple Risky Choices

Favre

Wittwer

Heinimann³

et al. 2016

PLoS ONE

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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.

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“…Typical values of the attraction factors are derived by Yukalov and Sornette (2016) in the general case of a decision involving more than two prospects.…”

Section: Quarter Law: Prediction Of Qdt On Attraction Factorsmentioning

confidence: 99%

Quantum Decision Theory in Simple Risky Choices

Favre

Wittwer

Heinimann³

et al. 2016

PLoS ONE

Self Cite

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“…It is worth stressing that the consensual limit (40), under conflicting initial conditions (38) or (39), satisfies the inequalities 0 < p * < 1 , which is proved as follows.…”

Section: Agents With Long-term Memorymentioning

confidence: 93%

“…Contrary to this, our QDT [37][38][39] is general, being formulated for arbitrary composite events. Its mathematics is based on the theory of quantum measurements [53][54][55], which allows it to be used also for the problem of creating artificial quantum intelligence [39,69,70].…”

Section: Main Features Of Quantum Approachmentioning

confidence: 99%

Information processing by networks of quantum decision makers

Yukalov

Yukalova

Sornette

2018

Physica A: Statistical Mechanics and its Applications

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We suggest a model of a multi-agent society of decision makers taking decisions being based on two criteria, one is the utility of the prospects and the other is the attractiveness of the considered prospects. The model is the generalization of quantum decision theory, developed earlier for single decision makers realizing one-step decisions, in two principal aspects. First, several decision makers are considered simultaneously, who interact with each other through information exchange. Second, a multistep procedure is treated, when the agents exchange information many times. Several decision makers exchanging information and forming their judgement, using quantum rules, form a kind of a quantum information network, where collective decisions develop in time as a result of information exchange. In addition to characterizing collective decisions that arise in human societies, such networks can describe dynamical processes occurring in artificial quantum intelligence composed of several parts or in a cluster of quantum computers. The practical usage of the theory is illustrated on the dynamic disjunction effect for which three quantitative predictions are made: (i) the probabilistic behavior of decision makers at the initial stage of the process is described; (ii) the decrease of the difference between the initial prospect probabilities and the related utility factors is proved; (iii) the existence of a common consensus after multiple exchange of information is predicted. The predicted numerical values are in very good agreement with empirical data.Keywords: Multi-agent society, artificial quantum intelligence, quantum decision theory, multistep decision procedure, dynamics of collective opinion, quantum information networks, intelligence networks, dynamic disjunction effect * Corresponding author: V.I. Yukalov

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“…In decision theory, the classical probability is responsible for a rational choice of alternatives and can be named rational fraction or utility fraction , since its value is prescribed by the utility of the alternative [ 25 , 46 , 65 , 71 , 72 ].…”

Section: Dual Decision Processmentioning

confidence: 99%

Evolutionary Processes in Quantum Decision Theory

Yukalov

2020

Entropy

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The review presents the basics of quantum decision theory, with an emphasis on temporary processes in decision making. The aim is to explain the principal points of the theory. How an operationally-testable, rational choice between alternatives differs from a choice decorated by irrational feelings is elucidated. Quantum-classical correspondence is emphasized. A model of quantum intelligence network is described. Dynamic inconsistencies are shown to be resolved in the frame of the quantum decision theory.

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Quantitative Predictions in Quantum Decision Theory

Cited by 51 publications

References 73 publications

Quantum Decision Theory in Simple Risky Choices

Quantum Decision Theory in Simple Risky Choices

Information processing by networks of quantum decision makers

Evolutionary Processes in Quantum Decision Theory

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