This article addresses the effectiveness of the predictive modeling of cognition and behavior based on quantum principles and some of the reasons for this effectiveness. It also aims, however, to explore the limitations of mathematical modeling so based, quantum-like (Q-L) modeling, and all mathematical modeling, including classical-like (C-L), in considering human cognition and behavior. It will discuss certain alternative approaches to both, essentially philosophical in nature, although sometimes found in literary works, approaches that, while not quantitative, may help compensate for limitations of mathematical modeling there. Most Q-L and C-L approaches beyond physics are realist, insofar as they offer representations of human thinking by the formalism of quantum or classical physical theories. The position adopted in this article is based on the non-realist assumption that such a representation may not be possible, which is not the same as that it is impossible. I designate interpretations that do not make this assumption reality-without-realism, RWR, interpretations, and in considering mental processes as ideality-without-idealism, IWI, interpretations.
This article addresses the effectiveness of the predictive modeling of cognition and behavior based on quantum principles and some of the reasons for this effectiveness. It also aims, however, to explore the limitations of mathematical modeling so based, quantum-like (Q-L) modeling, and all mathematical modeling, including classical-like (C-L), in considering human cognition and behavior. It will discuss certain alternative approaches to both, essentially philosophical in nature, although sometimes found in literary works, approaches that, while not quantitative, may help compensate for limitations of mathematical modeling there. Most Q-L and C-L approaches beyond physics are realist, insofar as they offer representations of human thinking by the formalism of quantum or classical physical theories. The position adopted in this article is based on the non-realist assumption that such a representation may not be possible, which is not the same as that it is impossible. I designate interpretations that do not make this assumption reality-without-realism, RWR, interpretations, and in considering mental processes as ideality-without-idealism, IWI, interpretations.
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.
Is mind quantum-like? Is consciousness quantum physical? Does consciousness have a role to play in the emergence of the classical world from the underlying quantum universe? Or is this dichotomy between classical and quantum an illusion? How can world philosophies enrich our views on these matters and interact with the best scientific theories? These are some questions that motivated us to conceive the current book. We also felt an urgent need to discuss the central philosophical questions haunting the emerging frameworks of quantum cognition and quantum-like framework (QLF). We have observed that there are very good technical or mathematical works being done in the emerging fields of quantum cognition and QLF, but there is still a great need for exploring the underlying and open philosophical questions they demand. Quantum cognition developed as a frontier research programme in understanding various cognitive phenomena that are hard or impossible to describe based on classical cognitive science paradigm. Classical cognitive science draws philosophically and mathematically from classical physics and classical probability theory. For example, cognitive realism thinking is deeply motivated by the scientific realism of classical physics. However, as we explore, there are numerous empirical findings which demonstrate clearly that human mind and cognitive processes exhibit features that are more quantum-like. Central to these features are indeterminacy, context dependence, and complementarity of cognitive phenomena, for example, perception, information retrieval, and even qualia. Many good works in the previous decade have demonstrated the efficacy of quantum-like mathematical modelling in such cases. However, given that efficacy, we cannot simply conclude that mind is quantum. Rather there are features that go beyond what is allowed in standard quantum formalism.
Contemporary discussions of the gap between natural and artificial intelligence often emphasize human capacities such as contextual reasoning, cognitive flexibility, and non-classical decision-making. This paper proposes that quantum and quantum-like models of cognition and decision processes offer a principled framework for addressing these differences. A growing body of empirical evidence shows that human reasoning systematically violates the assumptions of classical probability and logic, exhibiting contextuality, order effects, interference phenomena, and task incompatibility. Quantum probability theory and related quantum-like formalisms provide mathematically rigorous tools—based on Hilbert spaces, superposition, and entanglement—that capture these features more naturally than classical models. While quantum and quantum-like approaches share a common mathematical structure, they differ in physical implementation, motivating two complementary directions in artificial intelligence: quantum AI and quantum-like AI. Together, these approaches suggest a viable pathway toward narrowing, and potentially bridging, the divide between natural and artificial intelligence by grounding AI architectures in models aligned with the structure of human cognition.
This article examines some experimental conditions that invite and possibly require recourse to quantum-mechanical-like mathematical models (QMLMs), models based on the key mathematical features of quantum mechanics, in scientific fields outside physics, such as biology, cognitive psychology, or economics. In particular, I consider whether the following two correlative features of quantum phenomena that were decisive for establishing the mathematical formalism of quantum mechanics play similarly important roles in QMLMs elsewhere. The first is the individuality and discreteness of quantum phenomena, and the second is the irreducibly probabilistic nature of our predictions concerning them, coupled to the particular character of the probabilities involved, as different from the character of probabilities found in classical physics. I also argue that these features could be interpreted in terms of a particular form of epistemology that suspends and even precludes a causal and, in the first place, realist description of quantum objects and processes. This epistemology limits the descriptive capacity of quantum theory to the description, classical in nature, of the observed quantum phenomena manifested in measuring instruments. Quantum mechanics itself only provides descriptions, probabilistic in nature, concerning numerical data pertaining to such phenomena, without offering a physical description of quantum objects and processes. While QMLMs share their use of the quantum-mechanical or analogous mathematical formalism, they may differ by the roles, if any, the two features in question play in them and by different ways of interpreting the phenomena they considered and this formalism itself. This article will address those differences as well.
In this article, a novel approach to cognition inspired by quantum mechanical principles is proposed. It is based on an analogy between the physical objects at the quantum level and the human's mental states. Specifically, symbols in various cognitive functions are to be treated as eigenstates with respect to a particular quantum experimental arrangement. The arrangement is associated with an operator (called a formulation) corresponding to an observable of quantum mechanics. A state of affairs is treated as a superposition of eigenstates. Based on these assumptions, the quantum mechanical formalism can be straightforwardly applied to cognitive processes. As in quantum mechanics, there is an analogous Uncertainty Principle in representation. Furthermore, it is shown that non-monotonicity and counterfactual conditionals can be accommodated in a quantum mechanical framework.
While mathematical modeling beyond physics—in biology, neuroscience, psychology, and economics—has been and is still dominated by classical mathematical models (C-models), primarily of probabilistic and statistical nature, quantum mathematical models (Q-models), mathematical models based in the mathematical formalism of quantum theory, have recently acquired currency in mathematical modeling in these areas. This chapter examines some of the reasons for using such models. In order to do so, the author considers the fundamental principles behind these models in quantum physics itself, taking as its point of departure Einstein’s distinction between “constructive” and “principle” theories. Two types of principle thinking in quantum theory will be considered, those defining the initial development of quantum mechanics in 1920s and those of quantum information theory, a more recent and still ongoing development. The principle perspective, the author argues, may help us to understand better a possible and possibly necessary role for quantum mathematical models beyond physics.