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Quantum Models of Cognition and Decision-Making

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

Deadline for manuscript submissions: closed (1 May 2021) | Viewed by 34040

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Prof. Dr. Andrei Khrennikov

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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
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Prof. Dr. Fabio Bagarello

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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 idea is to represent both genuine quantum physical models and quantum-like models. The quantum models describe, in particular, the transition from quantum physical processes in the brain to cognition, consciousness, and decision-making, but not only: other applications, to different realms of science, are also interesting and successful. The quantum-like models do not refer necessarily 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. Andrei Khrennikov
Prof. 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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Research

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35 pages, 381 KiB

Open AccessArticle

On “Decisions and Revisions Which a Minute Will Reverse”: Consciousness, The Unconscious and Mathematical Modeling of Thinking

by Arkady Plotnitsky

Entropy 2021, 23(8), 1026; https://doi.org/10.3390/e23081026 - 09 Aug 2021

Cited by 5 | Viewed by 1743

Abstract

This article considers a partly philosophical question: What are the ontological and epistemological reasons for using quantum-like models or theories (models and theories based on the mathematical formalism of quantum theory) vs. classical-like ones (based on the mathematics of classical physics), in considering human thinking and decision making? This question is only partly philosophical because it also concerns the scientific understanding of the phenomena considered by the theories that use mathematical models of either type, just as in physics itself, where this question also arises as a physical question. This is because this question is in effect: What are the physical reasons for using, even if not requiring, these types of theories in considering quantum phenomena, which these theories predict fully in accord with the experiment? This is clearly also a physical, rather than only philosophical, question and so is, accordingly, the question of whether one needs classical-like or quantum-like theories or both (just as in physics we use both classical and quantum theories) in considering human thinking in psychology and related fields, such as decision science. It comes as no surprise that many of these reasons are parallel to those that are responsible for the use of QM and QFT in the case of quantum phenomena. Still, the corresponding situations should be understood and justified in terms of the phenomena considered, phenomena defined by human thinking, because there are important differences between these phenomena and quantum phenomena, which this article aims to address. In order to do so, this article will first consider quantum phenomena and quantum theory, before turning to human thinking and decision making, in addressing which it will also discuss two recent quantum-like approaches to human thinking, that by M. G. D’Ariano and F. Faggin and that by A. Khrennikov. Both approaches are ontological in the sense of offering representations, different in character in each approach, of human thinking by the formalism of quantum theory. Whether such a representation, as opposed to only predicting the outcomes of relevant experiments, is possible either in quantum theory or in quantum-like theories of human thinking is one of the questions addressed in this article. The philosophical position adopted in it is that it may not be possible to make this assumption, which, however, is not the same as saying that it is impossible. I designate this view as the reality-without-realism, RWR, view and in considering strictly mental processes as the ideality-without-idealism, IWI, view, in the second case in part following, but also moving beyond, I. Kant’s philosophy. Full article

(This article belongs to the Special Issue Quantum Models of Cognition and Decision-Making)

19 pages, 379 KiB

Open AccessArticle

A Quantum Walk Model for Idea Propagation in Social Network and Group Decision Making

by Qizi Zhang and Jerome Busemeyer

Entropy 2021, 23(5), 622; https://doi.org/10.3390/e23050622 - 16 May 2021

Cited by 4 | Viewed by 2544

Abstract

We propose a quantum walk model to investigate the propagation of ideas in a network and the formation of agreement in group decision making. In more detail, we consider two different graphs describing the connections of agents in the network: the line graph and the ring graph. Our main interest is to deduce the dynamics for such propagation, and to investigate the influence of compliance of the agents and graph structure on the decision time and the final decision. The methodology is based on the use of control-U gates in quantum computing. The original state of the network is used as controller and its mirrored state is used as target. The state of the quantum walk is the tensor product of the original state and the mirror state. In this way, the proposed quantum walk model is able to describe asymmetric influence between agents. Full article

(This article belongs to the Special Issue Quantum Models of Cognition and Decision-Making)

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13 pages, 4280 KiB

Open AccessArticle

Quantum Contagion: A Quantum-Like Approach for the Analysis of Social Contagion Dynamics with Heterogeneous Adoption Thresholds

by Ece C. Mutlu and Ozlem Ozmen Garibay

Entropy 2021, 23(5), 538; https://doi.org/10.3390/e23050538 - 27 Apr 2021

Cited by 6 | Viewed by 1803

Abstract

Modeling the information of social contagion processes has recently attracted a substantial amount of interest from researchers due to its wide applicability in network science, multi-agent-systems, information science, and marketing. Unlike in biological spreading, the existence of a reinforcement effect in social contagion necessitates considering the complexity of individuals in the systems. Although many studies acknowledged the heterogeneity of the individuals in their adoption of information, there are no studies that take into account the individuals’ uncertainty during their adoption decision-making. This resulted in less than optimal modeling of social contagion dynamics in the existence of phase transition in the final adoption size versus transmission probability. We employed the Inverse Born Problem (IBP) to represent probabilistic entities as complex probability amplitudes in edge-based compartmental theory, and demonstrated that our novel approach performs better in the prediction of social contagion dynamics through extensive simulations on random regular networks. Full article

(This article belongs to the Special Issue Quantum Models of Cognition and Decision-Making)

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18 pages, 310 KiB

Open AccessArticle

Order-Stability in Complex Biological, Social, and AI-Systems from Quantum Information Theory

by Andrei Khrennikov and Noboru Watanabe

Entropy 2021, 23(3), 355; https://doi.org/10.3390/e23030355 - 16 Mar 2021

Cited by 6 | Viewed by 1862

Abstract

This paper is our attempt, on the basis of physical theory, to bring more clarification on the question “What is life?” formulated in the well-known book of Schrödinger in 1944. According to Schrödinger, the main distinguishing feature of a biosystem’s functioning is the ability to preserve its order structure or, in mathematical terms, to prevent increasing of entropy. However, Schrödinger’s analysis shows that the classical theory is not able to adequately describe the order-stability in a biosystem. Schrödinger also appealed to the ambiguous notion of negative entropy. We apply quantum theory. As is well-known, behaviour of the quantum von Neumann entropy crucially differs from behaviour of classical entropy. We consider a complex biosystem S composed of many subsystems, say proteins, cells, or neural networks in the brain, that is,

S = (S_{i}) .

We study the following problem: whether the compound system S can maintain “global order” in the situation of an increase of local disorder and if S can preserve the low entropy while other

S_{i}

increase their entropies (may be essentially). We show that the entropy of a system as a whole can be constant, while the entropies of its parts rising. For classical systems, this is impossible, because the entropy of S cannot be less than the entropy of its subsystem

S_{i}

. And if a subsystems’s entropy increases, then a system’s entropy should also increase, by at least the same amount. However, within the quantum information theory, the answer is positive. The significant role is played by the entanglement of a subsystems’ states. In the absence of entanglement, the increasing of local disorder implies an increasing disorder in the compound system S (as in the classical regime). In this note, we proceed within a quantum-like approach to mathematical modeling of information processing by biosystems—respecting the quantum laws need not be based on genuine quantum physical processes in biosystems. Recently, such modeling found numerous applications in molecular biology, genetics, evolution theory, cognition, psychology and decision making. The quantum-like model of order stability can be applied not only in biology, but also in social science and artificial intelligence. Full article

(This article belongs to the Special Issue Quantum Models of Cognition and Decision-Making)

7 pages, 1231 KiB

Open AccessArticle

Using the Quantum Potential in Elementary Portfolio Management: Some Initial Ideas

by Hossein Khaksar, Emmanuel Haven, Sina Nasiri and Gholamreza Jafari

Entropy 2021, 23(2), 180; https://doi.org/10.3390/e23020180 - 30 Jan 2021

Cited by 2 | Viewed by 1886

Abstract

Owing to the globalization of the economy, the concept of entangled markets started to form, and this occurrence has smoothed the entrance of quantum mechanics into behavioral finance. In this manuscript, we introduce quantum risk and perform an analysis on portfolio optimization by controlling the quantum potential. We apply this method to eight major indices and construct a portfolio with a minimum quantum risk. The results show quantum risk has a power law behavior with a time-scale just as a standard deviation with different exponents. Full article

(This article belongs to the Special Issue Quantum Models of Cognition and Decision-Making)

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22 pages, 508 KiB

Open AccessArticle

Quantum-Like Interdependence Theory Advances Autonomous Human–Machine Teams (A-HMTs)

by William F. Lawless

Entropy 2020, 22(11), 1227; https://doi.org/10.3390/e22111227 - 28 Oct 2020

Cited by 18 | Viewed by 2652

Abstract

As humanity grapples with the concept of autonomy for human–machine teams (A-HMTs), unresolved is the necessity for the control of autonomy that instills trust. For non-autonomous systems in states with a high degree of certainty, rational approaches exist to solve, model or control stable interactions; e.g., game theory, scale-free network theory, multi-agent systems, drone swarms. As an example, guided by artificial intelligence (AI, including machine learning, ML) or by human operators, swarms of drones have made spectacular gains in applications too numerous to list (e.g., crop management; mapping, surveillance and fire-fighting systems; weapon systems). But under states of uncertainty or where conflict exists, rational models fail, exactly where interdependence theory thrives. Large, coupled physical or information systems can also experience synergism or dysergism from interdependence. Synergistically, the best human teams are not only highly interdependent, but they also exploit interdependence to reduce uncertainty, the focus of this work-in-progress and roadmap. We have long argued that interdependence is fundamental to human autonomy in teams. But for A-HMTs, no mathematics exists to build from rational theory or social science for their design nor safe or effective operation, a severe weakness. Compared to the rational and traditional social theory, we hope to advance interdependence theory first by mapping similarities between quantum theory and our prior findings; e.g., to maintain interdependence, we previously established that boundaries reduce dysergic effects to allow teams to function (akin to blocking interference to prevent quantum decoherence). Second, we extend our prior findings with case studies to predict with interdependence theory that as uncertainty increases in non-factorable situations for humans, the duality in two-sided beliefs serves debaters who explore alternatives with tradeoffs in the search for the best path going forward. Third, applied to autonomous teams, we conclude that a machine in an A-HMT must be able to express itself to its human teammates in causal language however imperfectly. Full article

(This article belongs to the Special Issue Quantum Models of Cognition and Decision-Making)

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14 pages, 1008 KiB

Open AccessArticle

Spreading of Competing Information in a Network

by Fabio Bagarello, Francesco Gargano and Francesco Oliveri

Entropy 2020, 22(10), 1169; https://doi.org/10.3390/e22101169 - 17 Oct 2020

Cited by 12 | Viewed by 1841

Abstract

We propose a simple approach to investigate the spreading of news in a network. In more detail, we consider two different versions of a single type of information, one of which is close to the essence of the information (and we call it good news), and another of which is somehow modified from some biased agent of the system (fake news, in our language). Good and fake news move around some agents, getting the original information and returning their own version of it to other agents of the network. Our main interest is to deduce the dynamics for such spreading, and to analyze if and under which conditions good news wins against fake news. The methodology is based on the use of ladder fermionic operators, which are quite efficient in modeling dispersion effects and interactions between the agents of the system. Full article

(This article belongs to the Special Issue Quantum Models of Cognition and Decision-Making)

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12 pages, 342 KiB

Open AccessFeature PaperArticle

Application of Quantum—Markov Open System Models to Human Cognition and Decision

by Jerome Busemeyer, Qizi Zhang, S. N. Balakrishnan and Zheng Wang

Entropy 2020, 22(9), 990; https://doi.org/10.3390/e22090990 - 04 Sep 2020

Cited by 14 | Viewed by 3293

Abstract

Markov processes, such as random walk models, have been successfully used by cognitive and neural scientists to model human choice behavior and decision time for over 50 years. Recently, quantum walk models have been introduced as an alternative way to model the dynamics of human choice and confidence across time. Empirical evidence points to the need for both types of processes, and open system models provide a way to incorporate them both into a single process. However, some of the constraints required by open system models present challenges for achieving this goal. The purpose of this article is to address these challenges and formulate open system models that have good potential to make important advancements in cognitive science. Full article

(This article belongs to the Special Issue Quantum Models of Cognition and Decision-Making)

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16 pages, 698 KiB

Open AccessFeature PaperArticle

Contextuality Analysis of Impossible Figures

by Víctor H. Cervantes and Ehtibar N. Dzhafarov

Entropy 2020, 22(9), 981; https://doi.org/10.3390/e22090981 - 03 Sep 2020

Cited by 5 | Viewed by 2713

Abstract

This paper has two purposes. One is to demonstrate contextuality analysis of systems of epistemic random variables. The other is to evaluate the performance of a new, hierarchical version of the measure of (non)contextuality introduced in earlier publications. As objects of analysis we use impossible figures of the kind created by the Penroses and Escher. We make no assumptions as to how an impossible figure is perceived, taking it instead as a fixed physical object allowing one of several deterministic descriptions. Systems of epistemic random variables are obtained by probabilistically mixing these deterministic systems. This probabilistic mixture reflects our uncertainty or lack of knowledge rather than random variability in the frequentist sense. Full article

(This article belongs to the Special Issue Quantum Models of Cognition and Decision-Making)

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21 pages, 1925 KiB

Open AccessFeature PaperArticle

Toward a Unified View of Cognitive and Biochemical Activity: Meditation and Linguistic Self-Reconstructing May Lead to Inflammation and Oxidative Stress Improvement

by Carlo Dal Lin, Laura Brugnolo, Mariela Marinova, Mario Plebani, Sabino Iliceto, Francesco Tona and Giuseppe Vitiello

Entropy 2020, 22(8), 818; https://doi.org/10.3390/e22080818 - 27 Jul 2020

Cited by 9 | Viewed by 2956

Abstract

Stress appears to be the basis of many diseases, especially myocardial infarction. Events are not objectively “stressful” but what is central is how the individual structures the experience he is facing: the thoughts he produces about an event put him under stress. This cognitive process could be revealed by language (words and structure). We followed 90 patients with ischemic heart disease and 30 healthy volunteers, after having taught them the Relaxation Response (RR) as part of a 4-day Rational–Emotional–Education intervention. We analyzed with the Linguistic Inquiry and Word Count software the words that the subjects used across the study following the progression of blood galectin-3 (inflammation marker) and malondialdehyde (oxidative stress marker). During the follow-up, we confirmed an acute and chronic decrease in the markers of inflammation and oxidative stress already highlighted in our previous studies together with a significant change in the use of language by the subjects of the RR groups. Our results and the precise design of our study would seem to suggest the existence of an intimate relationship and regulatory action by cognitive processes (recognizable by the type of language used) on some molecular processes in the human body. Full article

(This article belongs to the Special Issue Quantum Models of Cognition and Decision-Making)

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34 pages, 486 KiB

Open AccessFeature PaperArticle

A Unified Theory of Human Judgements and Decision-Making under Uncertainty

by Raffaele Pisano and Sandro Sozzo

Entropy 2020, 22(7), 738; https://doi.org/10.3390/e22070738 - 03 Jul 2020

Cited by 7 | Viewed by 2807

Abstract

Growing empirical evidence reveals that traditional set-theoretic structures cannot in general be applied to cognitive phenomena. This has raised several problems, as illustrated, for example, by probability judgement errors and decision-making (DM) errors. We propose here a unified theoretical perspective which applies the mathematical formalism of quantum theory in Hilbert space to cognitive domains. In this perspective, judgements and decisions are described as intrinsically non-deterministic processes which involve a contextual interaction between a conceptual entity and the cognitive context surrounding it. When a given phenomenon is considered, the quantum-theoretic framework identifies entities, states, contexts, properties and outcome statistics, and applies the mathematical formalism of quantum theory to model the considered phenomenon. We explain how the quantum-theoretic framework works in a variety of judgement and decision situations where systematic and significant deviations from classicality occur. Full article

(This article belongs to the Special Issue Quantum Models of Cognition and Decision-Making)

17 pages, 294 KiB

Open AccessArticle

Social Laser Model for the Bandwagon Effect: Generation of Coherent Information Waves

by Andrei Khrennikov

Entropy 2020, 22(5), 559; https://doi.org/10.3390/e22050559 - 17 May 2020

Cited by 8 | Viewed by 3145

Abstract

During recent years our society has often been exposed to coherent information waves of high amplitudes. These are waves of huge social energy. Often they are of destructive character, a kind of information tsunami. However, they can also carry positive improvements in human society, as waves of decision-making matching rational recommendations of societal institutes. The main distinguishing features of these waves are their high amplitude, coherence (homogeneous character of social actions generated by them), and short time needed for their generation and relaxation. Such waves can be treated as large-scale exhibitions of the bandwagon effect. We show that this socio-psychic phenomenon can be modeled based on the recently developed social laser theory. This theory can be used to model stimulated amplification of coherent social actions. “Actions” are treated very generally, from mass protests to votes and other collective decisions, such as, e.g., acceptance (often unconscious) of some societal recommendations. In this paper, we concentrate on the theory of laser resonators, physical vs. social. For the latter, we analyze in detail the functioning of Internet-based echo chambers. Their main purpose is increasing of the power of the quantum information field as well as its coherence. Of course, the bandwagon effect is well known and well studied in social psychology. However, social laser theory gives the possibility to model it by using general formalism of quantum field theory. The paper contains the minimum of mathematics and it can be read by researchers working in psychological, cognitive, social, and political sciences; it might also be interesting for experts in information theory and artificial intelligence. Full article

(This article belongs to the Special Issue Quantum Models of Cognition and Decision-Making)

Review

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31 pages, 399 KiB

Open AccessReview

Evolutionary Processes in Quantum Decision Theory

by Vyacheslav I. Yukalov

Entropy 2020, 22(6), 681; https://doi.org/10.3390/e22060681 - 18 Jun 2020

Cited by 20 | Viewed by 2864

Abstract

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. Full article

(This article belongs to the Special Issue Quantum Models of Cognition and Decision-Making)

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