Quantum cognition models of ethical decision-making in human behavior simulation

Siamak Noorolahi

Levent Yılmaz

Multi-agent systems are widely used in implementing systems with autonomous behaviour, as well as simulating models that involve human behaviour. Ethical decision-making is a unique aspect of such socio-cognitive systems. In situations that require deliberation over a multitude of options with ethical implications, moral dilemmas are often resolved by a range of heuristics and principles that view the situation from different perspectives. While constraint and utility-driven decision-making strategies are customary in agent-based models, the incompatibility among multiple perspectives can invalidate the underlying premises of models of probabilistic utility-based decisions that rely on classic Kolmogorov axioms. In this paper, we highlight the fallacies of such models and present a practical case study to demonstrate how quantum cognition models can provide an alternative and credible representation of decision-making behaviour in simulations that involve ethical dilemmas.

William H. Batchelder, Hans Colonius, Ehtibar N. Dzhafarov

Zhong CHEN

Quantum computing introduces a transformative approach to social science research by integrating quantum probability models into social interaction experiments. This study examines the effects of quantum superposition, measurement-induced state collapse, and interference on decision-making processes. Compared to classical probability models, quantum approaches offer a more accurate representation of cognitive uncertainty, preference reversals, and contextual dependencies. The research highlights the advantages of quantum measurement in survey design, behavioral analysis, and policy simulations. However, challenges remain, including the limitations of current quantum hardware, the interdisciplinary gap between quantum mechanics and social sciences, and ethical concerns regarding data security and experimental manipulation. Future research should focus on refining quantum experimental methodologies, enhancing computational capabilities, and developing ethical guidelines for quantum-driven social science applications. By addressing these challenges, quantum computing can provide new theoretical insights and practical advancements in understanding human behavior and collective decision-making.

Andrei Yu. Khrennikov

Albert Barqué-Duran

The present thesis (mostly) concerns the application of alternative mathematical methods to understand patterns in human cognition and to model them. The different chapters presented in this thesis show research that concerns the application of quantum probability (QP) theory in the modeling of human decision-making. Quantum probability (QP) theory is a theory for how to assign probabilities to events. QP theory can be thought of as the probability rules from quantum mechanics, without any of the physics. This work is not about the application of quantum physics to brain physiology. Rather, we are interested in QP theory as a mathematical framework for cognitive modelling. This theory is potentially relevant in any behavioural situation that involves uncertainty. QP theory is analogous to classical probability theory, though QP theory and classical probability (CP) theory are founded from different sets of axioms (the Kolmogorov and Dirac/von Neumann axioms respectively) and so are subject to alternative constraints. In this thesis we show that especially over the last decade, there has been a growing interest in decision-making and cognitive models using a quantum probabilistic (QP) framework. We see how this development encompasses publications in major journals (see Pothos and Busemeyer, 2013; Wang et al., 2014; and Yearsley and Pothos, 2014; among others), special issues, and dedicated workshops, as well as several comprehensive books (Busemeyer and Bruza, 2012; Khrennikov, 2010; and Haven and Khrennikov, 2010). However, uncertainty itself is neither ethical nor unethical – yet it is inherent to most situations in which, for instance, moral judgments and decisions have to be made. For a descriptive understanding of judgment and decisions in moral situations, it is an important lesson to acknowledge both the cognitive side (bounded rationality) and the environment (ecological rationality) – and thus the uncertainty of the world and how the mind deals with it. This thesis also shows significant interest in moral and social psychology. Specifically, we consider present technologies that suggest a need for evaluating alternative contexts for ethical decision-making. How the research on human-machine interaction feeds back into humans’ understanding of themselves as moral agents? This key question ultimately relates to the nature of ethical theory itself. Overall, this dissertation presents and addresses not only standard aspects of decision- making processes, such as similarity judgments (Chapters 1 to 4) or the constructive role of articulating impressions (Chapter 5), but also standard aspects of social psychology, such as moral judgments (Chapters 6 and 7) and game theory (Chapter 8). As stated in the Declarations section, the present thesis is a combination of a standard and a publication- based dissertation.