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Psychological 'double-slit experiment' in decision making: Quantum versus classical
RAS, Russia.ORCID iD: 0000-0001-5683-5988
Linnaeus University, Faculty of Technology, Department of Mathematics. Natl Res Univ Informat Technol Mech & Opt ITMO, Russia. (Int Ctr Math Modeling Phys Engn Econ & Cognit Sci)ORCID iD: 0000-0002-9857-0938
2020 (English)In: Biosystems (Amsterdam. Print), ISSN 0303-2647, E-ISSN 1872-8324, Vol. 195, p. 1-11, article id 104171Article in journal (Refereed) Published
Abstract [en]

This paper is devoted to justification of the application of quantum probability theory to problems of cognition, psychology, and decision making. Such applications are heavily based on quantum-like representation of interference of events that is formalized with complex probability amplitudes ("mental wave functions") and the Born rule for calculation of probability. In this paper, we present universal mathematical formalization of interference of events based on the calculus of intensities of interacting processes. Generally, this formalization leads to the nonlinear law of superposition of complex probability amplitudes with quantum linear superposition as a special important case. For intensities characterized by discrete occurrence of events, the formula for interference of intensities is transferred into the quantum-like formula for interference of probabilities. We illustrate the formalism by simple examples of possible applications of the calculus of intensities of processes to decision making and economics. We show that in special cases the classical (Kolmogorov) probabilistic model can give the same results as the quantum rule of summation of probabilities.

Place, publisher, year, edition, pages
Elsevier, 2020. Vol. 195, p. 1-11, article id 104171
Keywords [en]
Quantum-like models, Linear and nonlinear interference of probabilities, Born's rule, Contextuality, Decision making, Intensity of process, Social science, Economics
National Category
Mathematics
Research subject
Natural Science, Mathematics
Identifiers
URN: urn:nbn:se:lnu:diva-97721DOI: 10.1016/j.biosystems.2020.104171ISI: 000551338300009PubMedID: 32485348Scopus ID: 2-s2.0-85085892378OAI: oai:DiVA.org:lnu-97721DiVA, id: diva2:1461786
Available from: 2020-08-27 Created: 2020-08-27 Last updated: 2021-05-07Bibliographically approved

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Khrennikov, Andrei

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