On the surface, behavioural data science and physics seem to be two disparate fields of research. However, a closer examination of problems solved by them reveals that they are uniquely related to one another. Exemplified by the theories of quantum mind, cognition and decision-making, this unique relationship serves as the topic of this chapter. Surveying the current academic journal papers and scholarly monographs, we present an alternative vision of the role of quantum mechanics in the modern studies of human perception, behaviour and decision-making. To that end, we mostly aim to answer the ‘ how ’ question, deliberately avoiding complex mathematical concepts but developing a technically simple computational code that the readers can modify to design their own quantum-inspired models. We also present several practical examples of the application of the computation code and outline several plausible scenarios, where quantum models based on the proposed do-it-yourself model kit can help understand the differences between the behaviour of individuals and social groups.
On the surface, behavioural data science and physics seem to be two disparate fields of research. However, a closer examination of problems solved by them reveals that they are uniquely related to one another. Exemplified by the theories of quantum mind, cognition and decision-making, this unique relationship serves as the topic of this chapter. Surveying the current academic journal papers and scholarly monographs, we present an alternative vision of the role of quantum mechanics in the modern studies of human perception, behaviour and decision-making. To that end, we mostly aim to answer the ‘ how ’ question, deliberately avoiding complex mathematical concepts but developing a technically simple computational code that the readers can modify to design their own quantum-inspired models. We also present several practical examples of the application of the computation code and outline several plausible scenarios, where quantum models based on the proposed do-it-yourself model kit can help understand the differences between the behaviour of individuals and social groups.
On the surface, behavioural science and physics seem to be two disparate fields of research. However, a closer examination of problems solved by them reveals that they are uniquely related to one another. Exemplified by the theories of quantum mind, cognition and decision-making, this unique relationship serves as the topic of this chapter. Surveying the current academic journal papers and scholarly monographs, we present an alternative vision of the role of quantum mechanics in the modern studies of human perception, behaviour and decision-making. To that end, we mostly aim to answer the 'how' question, deliberately avoiding complex mathematical concepts but developing a technically simple computational code that the readers can modify to design their own quantum-inspired models. We also present several practical examples of the application of the computation code and outline several plausible scenarios, where quantum models based on the proposed do-it-yourself model kit can help understand the differences between the behaviour of individuals and social groups.
At first glance, quantum mechanics and behavioural science seem worlds apart---one rooted in equations and particles, the other in thoughts and choices. Yet, emerging research reveals a profound and unexpected bridge between them. This chapter explores that bridge through quantum models of cognition and decision-making, showing how principles from quantum mechanics can help understand, and even predict, the complexities of human perception, behaviour and societal dynamics. We introduce a computationally accessible framework grounded in quantum theory, designed to model ambiguity, bias and choice in a way that classical logic cannot. Drawing on interdisciplinary sources, we demonstrate how this approach not only enriches our understanding of individual cognition but also extends to AI, video game design, financial behaviour and collective decision-making in society. Through vivid case studies---from optical illusions in video games to decision biases in economic, defence and political contexts---we show how quantum models offer new explanatory and predictive power. Thus, this chapter invites readers from all professional backgrounds to reimagine cognition and decision-making, opening new avenues for science, technology and human understanding.
At first glance, quantum mechanics and behavioural science seem worlds apart -- one rooted in equations and particles, the other in thoughts and choices. Yet, emerging research reveals a profound and unexpected bridge between them. This chapter explores that bridge through quantum models of cognition and decision-making, showing how principles from quantum mechanics can help understand, and even predict, the complexities of human perception, behaviour and societal dynamics. We introduce a computationally accessible framework grounded in quantum theory, designed to model ambiguity, bias and choice in a way that classical logic cannot. Drawing on interdisciplinary sources, we demonstrate how this approach not only enriches our understanding of individual cognition but also extends to AI, video game design, financial behaviour and collective decision-making in society. Through vivid case studies -- from optical illusions in video games to decision biases in economic, defence and political contexts -- we show how quantum models offer new explanatory and predictive power. Thus, this chapter invites readers from all professional backgrounds to reimagine cognition and decision-making, opening new avenues for science, technology and human understanding.
Cognitive Science is the study of the mind and how it relates to human behaviour. As a field, it is highly interdisciplinary, bringing together theories from Psychology, Neuroscience, Biology, and others. The field of cognitive science operates at a number of levels. On the one hand, some aspects of cognitive science look at the behaviour of neurons, whereas other aspects look to explain human behaviour at a more abstract level, seeking to explain human decision making or reasoning. A key area of research in cognitive science is how to formalise human behaviours around judgements of similarity, categorization, and decision making. In the field of Physics, Quantum Mechanics has fundamentally altered our understanding of the way in which particles behave. Quantum mechanics has a number of unintuitive phenomena, some of which can be used model unusual aspects of human behaviour. The application of quantum theory to model human behaviour is wide-ranging. In this chapter we will look at three main areas in which it has been applied. One key area is in how similarity judgements can be modelled. There are a number of phenomena around similarity judgements that are not well modelled using a view of concepts that does not take the state of the observer into account. These include the asymmetry of similarity judgements and the fact that similarity can change depending on other exemplars that are present. Another key area is in judgement and decision-making. Again, puzzling phenomena have been observed regarding the fact that judgements do not follow classical probability theory, known as the conjunction fallacy, can depend crucially on the order in which questions are presented or on the amount of knowledge about the world. Finally, approaches to modelling cognitive phenomena at the neural level will also be discussed within a quantum-theoretic framework.
The article presents a review of foreign scientific literature on the quantum-like approach to understanding the modeling of cognition and decision-making processes. It is shown that the current application of quantum physics approaches to consciousness, psychological approaches such as perception, cognition, emotions, consciousness and learning, involves the search for a single objective mathematical model of what underlies the experience of the brain. The use of quantum physics algorithms can help in understanding the mechanisms of brain malfunctions and memory impairments that are found in pathologies such as dementia caused by Alzheimer's disease, schizophrenia, etc. Quantum physics approaches are applicable to issues of modeling cognition and decision-making processes, as well as in cognitive research, information processing by the human brain, artificial intelligence development, psychology, social and political sciences. Application of the abstract mathematical principles of quantum theory can help in understanding human consciousness and behavior. Quantum probability theory is applied to modeling human behavior due to the prevalence of uncertainty in human interaction with the world. Quantum cognitive models are especially useful in research in such areas as errors in decision making, order effects of questions, conceptual combinations, accumulation of evidence, perception, etc. Of particular interest to researchers are issues of quantum-like modeling of cognition and decision-making processes, the apparatus of quantum information and probability theory, useful for such modeling, as well as the use of such apparatus in cognitive research, the development of artificial intelligence, psychology, social and political sciences.
ABSTRACT Recent advances at the intersection of quantum physics, neuroscience, and cognitive science have renewed interest in whether quantum phenomena and quantum‐inspired formalisms can inform models of human cognition and decision‐making. While classical neural and computational models explain many aspects of perception and behavior, they face limitations in accounting for contextuality, order effects, probabilistic reasoning violations, ambiguity resolution, and rapid information integration. This review synthesizes evidence and theoretical frameworks linking quantum‐related principles to cognition, with emphasis on quantum sensing in biological systems, molecular and subcellular quantum‐relevant mechanisms, quantum‐to‐classical transition pathways, quantum‐inspired models of perception and decision‐making, and quantum‐inspired computational approaches. It also extends beyond the probabilistic arm of quantum cognition by considering emerging equilibrium‐based and causal‐logical theories, including mental equilibrium, brain‐universe similarity, mind‐light‐matter unity, quantum emergence, and quantum intelligence. Throughout, the review distinguishes physically instantiated quantum mechanisms from abstract quantum‐like formalisms that model contextuality, mental entanglement, and non‐separable cognitive dynamics without requiring sustained macroscopic quantum coherence in the brain. Finally, it identifies methodological challenges and future directions for advancing quantum cognitive science toward experimentally testable and biologically meaningful theories.