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Information processing by networks of quantum decision makers

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  • Yukalov, V.I.
  • Yukalova, E.P.
  • Sornette, D.

Abstract

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 judgment, 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.

Suggested Citation

  • Yukalov, V.I. & Yukalova, E.P. & Sornette, D., 2018. "Information processing by networks of quantum decision makers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 747-766.
    • Handle: RePEc:eee:phsmap:v:492:y:2018:i:c:p:747-766
    DOI: 10.1016/j.physa.2017.11.004
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    Citations

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    Cited by:

    1. Stan Lipovetsky, 2023. "Quantum-like Data Modeling in Applied Sciences: Review," Stats, MDPI, vol. 6(1), pages 1-9, February.
    2. Zhou, Boling & Yang, Yongqing & Xu, Xianyun, 2019. "The group-delay consensus for second-order multi-agent systems by piecewise adaptive pinning control in part of time interval," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 694-708.
    3. Benno Torgler, 2021. "Behavioral Taxation: Opportunities and Challenges," CREMA Working Paper Series 2021-25, Center for Research in Economics, Management and the Arts (CREMA).
    4. Ferro, Giuseppe M. & Kovalenko, Tatyana & Sornette, Didier, 2021. "Quantum decision theory augments rank-dependent expected utility and Cumulative Prospect Theory," Journal of Economic Psychology, Elsevier, vol. 86(C).
    5. Stan Lipovetsky & Michael Conklin, 2018. "Decreasing Respondent Heterogeneity by Likert Scales Adjustment via Multipoles," Stats, MDPI, vol. 1(1), pages 1-7, November.
    6. Steve J. Bickley & Ho Fai Chan & Sascha L. Schmidt & Benno Torgler, 2021. "Quantum-Sapiens: The Quantum Bases for Human Expertise, Knowledge, and Problem-Solving (Extended Version with Applications)," CREMA Working Paper Series 2021-14, Center for Research in Economics, Management and the Arts (CREMA).
    7. Yukalov, V.I. & Yukalova, E.P. & Sornette, D., 2022. "Role of collective information in networks of quantum operating agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 598(C).

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