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Entropy
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Quantum Models of Cognition and Decision-Making II
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Quantum Models of Cognition and Decision-Making II

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Quantum Information".

Deadline for manuscript submissions: closed (31 January 2024) | Viewed by 12018

Special Issue Editors

Prof. Dr. Andrei Khrennikov

E-Mail Website
Guest Editor
International Center for Mathematical Modeling in Physics and Cognitive Sciences, Linnaeus University, SE-351 95 Växjö, Sweden
Interests: quantum foundations; information; probability; contextuality; applications of the mathematical formalism of quantum theory outside of physics: cognition, psychology, decision making, economics, finances, and social and political sciences; p-adic numbers; p-adic and ultrametric analysis; dynamical systems; p-adic theoretical physics; utrametric models of cognition and psychological behavior; p-adic models in geophysics and petroleum research
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Fabio Bagarello

E-Mail Website
Guest Editor
Dipartimento di Ingegneria, Università di Palermo, Viale delle Scienze, 90128 Palermo, Italy
Interests: applications of quantum tools in macroscopic systems: social science, biology, ecology, finance; quantum decision making; dynamical systems; functional analysis; operator theory; deformed canonical commutation and anticommutation relations; ladder operators; non self-adjoint Hamiltonians; coherent states; quantization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In this Special Issue, we would like to emphasize the tremendous success in the application of quantum theory to modeling of cognition and decision making. Our aim is to represent both genuine quantum physical models and quantum-like models. Quantum models describe, in particular, the transition from quantum physical processes in the brain to cognition, consciousness, and decision making, but this not their only use: other applications, to different realms of science, are also interesting and successful. Quantum-like models do not necessarily refer explicitly to quantum physics. These models are based on operational exploration of the methodology and formalism of quantum theory.

The areas covered include:

  • Quantum physical processes in the brain and cognition;
  • Physics and consciousness;
  • Mapping brain areas involved in quantum information processing;
  • Applications to medicine;
  • Quantum-like models of cognition and decision making;
  • Applications to psychology, economics, finance, social, and political science;
  • Quantum information viewpoint to cognition;
  • Quantum foundations and cognition;
  • Generalized probabilistic models for decision making;
  • Quantum contextuality and generalized contextual models in psychology, economics, and social science;
  • Bell’s inequality, entanglement with applications to decision making;
  • The role of the complementarity principle in quantum-like modeling;
  • Quantum dynamics with applications to decision making, social and political science, ecology, evolution theory;
  • Quantum field theory with applications to modeling of the process of decision making;
  • Social laser model (social and political science, color revolutions, elections);
  • Applications to biology and ecology;
  • Order effects in decision making.

Of course, possible topics need not be restricted to the list above.

Prof. Dr. Andrei Khrennikov
Prof. Dr. Fabio Bagarello
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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Published Papers (7 papers)

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Research

19 pages, 2297 KiB  
Article
Random Lasers as Social Processes Simulators
by Alexander Alodjants, Peter Zacharenko, Dmitry Tsarev, Anna Avdyushina, Mariya Nikitina, Andrey Khrennikov and Alexander Boukhanovsky
Entropy 2023, 25(12), 1601; https://doi.org/10.3390/e25121601 - 29 Nov 2023
Cited by 4 | Viewed by 1400
Abstract
In this work, we suggest a quantum-like simulator concept to study social processes related to the solution of NP-hard problems. The simulator is based on the solaser model recently proposed by us in the framework of information cascade growth and echo chamber formation [...] Read more.
In this work, we suggest a quantum-like simulator concept to study social processes related to the solution of NP-hard problems. The simulator is based on the solaser model recently proposed by us in the framework of information cascade growth and echo chamber formation in social network communities. The simulator is connected with the random laser approach that we examine in the A and D-class (superradiant) laser limits. Novel network-enforced cooperativity parameters of decision-making agents, which may be measured as a result of the solaser simulation, are introduced and justified for social systems. The innovation diffusion in complex networks is discussed as one of the possible impacts of our proposal. Full article
(This article belongs to the Special Issue Quantum Models of Cognition and Decision-Making II)
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19 pages, 1048 KiB  
Article
Spreading of Information on a Network: A Quantum View
by Fabio Bagarello, Francesco Gargano, Matteo Gorgone and Francesco Oliveri
Entropy 2023, 25(10), 1438; https://doi.org/10.3390/e25101438 - 11 Oct 2023
Viewed by 1064
Abstract
This paper concerns the modeling of the spread of information through a complex, multi-layered network, where the information is transferred from an initial transmitter to a final receiver. The mathematical model is deduced within the framework of operatorial methods, according to the formal [...] Read more.
This paper concerns the modeling of the spread of information through a complex, multi-layered network, where the information is transferred from an initial transmitter to a final receiver. The mathematical model is deduced within the framework of operatorial methods, according to the formal mathematical apparatus typical of quantum mechanics. Two different approaches are considered: one based on the (H,ρ)-induced dynamics and one on the Gorini–Kossakowski–Sudarshan–Lindblad (GKSL) equation. For each method, numerical results are presented. Full article
(This article belongs to the Special Issue Quantum Models of Cognition and Decision-Making II)
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31 pages, 941 KiB  
Article
A Quantum-like Model of Interdependence for Embodied Human–Machine Teams: Reviewing the Path to Autonomy Facing Complexity and Uncertainty
by William F. Lawless, Ira S. Moskowitz and Katarina Z. Doctor
Entropy 2023, 25(9), 1323; https://doi.org/10.3390/e25091323 - 11 Sep 2023
Viewed by 1653
Abstract
In this review, our goal is to design and test quantum-like algorithms for Artificial Intelligence (AI) in open systems to structure a human–machine team to be able to reach its maximum performance. Unlike the laboratory, in open systems, teams face complexity, uncertainty and [...] Read more.
In this review, our goal is to design and test quantum-like algorithms for Artificial Intelligence (AI) in open systems to structure a human–machine team to be able to reach its maximum performance. Unlike the laboratory, in open systems, teams face complexity, uncertainty and conflict. All task domains have complexity levels—some low, and others high. Complexity in this new domain is affected by the environment and the task, which are both affected by uncertainty and conflict. We contrast individual and interdependence approaches to teams. The traditional and individual approach focuses on building teams and systems by aggregating the best available information for individuals, their thoughts, behaviors and skills. Its concepts are characterized chiefly by one-to-one relations between mind and body, a summation of disembodied individual mental and physical attributes, and degrees of freedom corresponding to the number of members in a team; however, this approach is characterized by the many researchers who have invested in it for almost a century with few results that can be generalized to human–machine interactions; by the replication crisis of today (e.g., the invalid scale for self-esteem); and by its many disembodied concepts. In contrast, our approach is based on the quantum-like nature of interdependence. It allows us theorization about the bistability of mind and body, but it poses a measurement problem and a non-factorable nature. Bistability addresses team structure and performance; the measurement problem solves the replication crisis; and the non-factorable aspect of teams reduces the degrees of freedom and the information derivable from teammates to match findings by the National Academies of Science. We review the science of teams and human–machine team research in the laboratory versus in the open field; justifications for rejecting traditional social science while supporting our approach; a fuller understanding of the complexity of teams and tasks; the mathematics involved; a review of results from our quantum-like model in the open field (e.g., tradeoffs between team structure and performance); and the path forward to advance the science of interdependence and autonomy. Full article
(This article belongs to the Special Issue Quantum Models of Cognition and Decision-Making II)
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9 pages, 472 KiB  
Article
Quantum Bohmian-Inspired Potential to Model Non–Gaussian Time Series and Its Application in Financial Markets
by Reza Hosseini, Samin Tajik, Zahra Koohi Lai, Tayeb Jamali, Emmanuel Haven and Reza Jafari
Entropy 2023, 25(7), 1061; https://doi.org/10.3390/e25071061 - 14 Jul 2023
Viewed by 1223
Abstract
We have implemented quantum modeling mainly based on Bohmian mechanics to study time series that contain strong coupling between their events. Compared to time series with normal densities, such time series are associated with rare events. Hence, employing Gaussian statistics drastically underestimates the [...] Read more.
We have implemented quantum modeling mainly based on Bohmian mechanics to study time series that contain strong coupling between their events. Compared to time series with normal densities, such time series are associated with rare events. Hence, employing Gaussian statistics drastically underestimates the occurrence of their rare events. The central objective of this study was to investigate the effects of rare events in the probability densities of time series from the point of view of quantum measurements. For this purpose, we first model the non-Gaussian behavior of time series using the multifractal random walk (MRW) approach. Then, we examine the role of the key parameter of MRW, λ, which controls the degree of non-Gaussianity, in quantum potentials derived for time series. Our Bohmian quantum analysis shows that the derived potential takes some negative values in high frequencies (its mean values), then substantially increases, and the value drops again for rare events. Thus, rare events can generate a potential barrier in the high-frequency region of the quantum potential, and the effect of such a barrier becomes prominent when the system transverses it. Finally, as an example of applying the quantum potential beyond the microscopic world, we compute quantum potentials for the S&P financial market time series to verify the presence of rare events in the non-Gaussian densities and demonstrate deviation from the Gaussian case. Full article
(This article belongs to the Special Issue Quantum Models of Cognition and Decision-Making II)
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16 pages, 321 KiB  
Article
The Modal Components of Judgements in a Quantum Model of Psychoanalytic Theory
by Giulia Battilotti, Miloš Borozan and Rosapia Lauro Grotto
Entropy 2023, 25(7), 1057; https://doi.org/10.3390/e25071057 - 13 Jul 2023
Cited by 1 | Viewed by 1230
Abstract
In the present paper, we develop a theory of thinking based on an attempt to formalize the construction of mental representations as described in psychoanalytic theory. In previous work, we described Freud’s and Matte Blanco’s structural Unconscious in a formal model in which [...] Read more.
In the present paper, we develop a theory of thinking based on an attempt to formalize the construction of mental representations as described in psychoanalytic theory. In previous work, we described Freud’s and Matte Blanco’s structural Unconscious in a formal model in which the properties of unconscious representations are captured by particular sets-infinite singletons-that can be derived in first-order logic language. Here, we afford the issue of the finitization of unconscious representations by assuming that the mind can form an all-purpose modality, originating from abstraction from infinite singletons; in this way, a symmetric prelogical setting for mental representations is formally created, and this is interpreted in a quantum spin model by a modal (necessity) projector. Then, by introducing time, one can describe the links that mental representations can establish with reality, and hence finitize the representations. The modality is so split into finite components, here termed positive, negative and irreal; the splitting of the modality is traced back to the decomposition of the spin observables by means of the Pauli matrices, which can offer a quantum semantics to the method applied. Here, we suggest that the development of the modal approach and its quantum logic implementation can be considered as a proper formalization of some aspect of the psychoanalytic theory of thinking proposed by Bion; namely, we will show that the process of abstraction leading from raw data to preconceptions, and therefore to the definition of the content-container relationship, is adequately captured by our model, and further correspondences can be detected with Bion’s theory about links and transformations, implying different ways in which the mind can get in touch with both internal and external reality. Full article
(This article belongs to the Special Issue Quantum Models of Cognition and Decision-Making II)
10 pages, 286 KiB  
Article
Behavioral Capital Theory via Canonical Quantization
by Raymond J. Hawkins and Joseph L. D’Anna
Entropy 2022, 24(10), 1497; https://doi.org/10.3390/e24101497 - 20 Oct 2022
Cited by 1 | Viewed by 1808
Abstract
We show how a behavioral form of capital theory can be derived using canonical quantization. In particular, we introduce quantum cognition into capital theory by applying Dirac’s canonical quantization approach to Weitzman’s Hamiltonian formulation of capital theory, the justification for the use of [...] Read more.
We show how a behavioral form of capital theory can be derived using canonical quantization. In particular, we introduce quantum cognition into capital theory by applying Dirac’s canonical quantization approach to Weitzman’s Hamiltonian formulation of capital theory, the justification for the use of quantum cognition being the incompatibility of questions encountered in the investment decision-making process. We illustrate the utility of this approach by deriving the capital-investment commutator for a canonical dynamic investment problem. Full article
(This article belongs to the Special Issue Quantum Models of Cognition and Decision-Making II)
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15 pages, 615 KiB  
Article
More Causes Less Effect: Destructive Interference in Decision Making
by Irina Basieva, Vijitashwa Pandey and Polina Khrennikova
Entropy 2022, 24(5), 725; https://doi.org/10.3390/e24050725 - 20 May 2022
Cited by 5 | Viewed by 2139
Abstract
We present a new experiment demonstrating destructive interference in customers’ estimates of conditional probabilities of product failure. We take the perspective of a manufacturer of consumer products and consider two situations of cause and effect. Whereas, individually, the effect of the causes is [...] Read more.
We present a new experiment demonstrating destructive interference in customers’ estimates of conditional probabilities of product failure. We take the perspective of a manufacturer of consumer products and consider two situations of cause and effect. Whereas, individually, the effect of the causes is similar, it is observed that when combined, the two causes produce the opposite effect. Such negative interference of two or more product features may be exploited for better modeling of the cognitive processes taking place in customers’ minds. Doing so can enhance the likelihood that a manufacturer will be able to design a better product, or a feature within it. Quantum probability has been used to explain some commonly observed “non-classical” effects, such as the disjunction effect, question order effect, violation of the sure-thing principle, and the Machina and Ellsberg paradoxes. In this work, we present results from a survey on the impact of multiple observed symptoms on the drivability of a vehicle. The symptoms are assumed to be conditionally independent. We demonstrate that the response statistics cannot be directly explained using classical probability, but quantum formulation easily models it, as it allows for both positive and negative “interference” between events. Since quantum formalism also accounts for classical probability’s predictions, it serves as a richer paradigm for modeling decision making behavior in engineering design and behavioral economics. Full article
(This article belongs to the Special Issue Quantum Models of Cognition and Decision-Making II)
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