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Cognition in Superposition: Quantum Models in AI, Finance, Defence, Gaming and Collective Behaviour
Ivan S. Maksymov
https://arxiv.org/abs/2508.20098 https://

Cognition in Superposition: Quantum Models in AI, Finance, Defence, Gaming and Collective Behaviour
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 compu…

Collective dynamics of strategic classification
Marta C. Couto, Flavia Barsotti, Fernando P. Santos
https://arxiv.org/abs/2508.09340 https://arxiv.org/pdf/…

Collective dynamics of strategic classification
Classification algorithms based on Artificial Intelligence (AI) are nowadays applied in high-stakes decisions in finance, healthcare, criminal justice, or education. Individuals can strategically adapt to the information gathered about classifiers, which in turn may require algorithms to be re-trained. Which collective dynamics will result from users' adaptation and algorithms' retraining? We apply evolutionary game theory to address this question. Our framework provides a mathematically rigoro…

Ethical AI: Towards Defining a Collective Evaluation Framework
Aasish Kumar Sharma, Dimitar Kyosev, Julian Kunkel
https://arxiv.org/abs/2506.00233 https://…

Ethical AI: Towards Defining a Collective Evaluation Framework
Artificial Intelligence (AI) is transforming sectors such as healthcare, finance, and autonomous systems, offering powerful tools for innovation. Yet its rapid integration raises urgent ethical concerns related to data ownership, privacy, and systemic bias. Issues like opaque decision-making, misleading outputs, and unfair treatment in high-stakes domains underscore the need for transparent and accountable AI systems. This article addresses these challenges by proposing a modular ethical assess…

The Mathematical Theory of Behavioural Swarms: Towards Modelling the Collective Dynamics of Living Systems
Rene Fabregas (University of Granada), Jie Liao (Shanghai University of Finance,Economics), Nisrine Outada (University Cadi Ayyad,UMMISCO, IRD-SU)
https://arxiv.org/abs/2508.12183

The Mathematical Theory of Behavioural Swarms: Towards Modelling the Collective Dynamics of Living Systems
Classical swarm models, exemplified by the Cucker--Smale framework, provide foundational insights into collective alignment but exhibit fundamental limitations in capturing the adaptive, heterogeneous behaviours intrinsic to living systems. This paper formalises the mathematical theory of \textit{Behavioural Swarms}, a comprehensive framework where each particle's state incorporates a dynamic internal variable, the \textit{activity} that co-evolves with position and velocity through nonlocal in…