The field of dynamical systems is being transformed by the mathematical tools and
algorithms emerging from modern computing and data science. First-principles derivations …

The dynamical behavior of social systems can be described by agent-based models.
Although single agents follow easily explainable rules, complex time-evolving patterns …

Understanding decision-making in dynamic and complex settings is a challenge yet
essential for preventing, mitigating, and responding to adverse events (eg, disasters …

Koopman operator theory is shown to be directly related to the renormalization group. This
observation allows us, with no assumption of translational invariance, to compute the critical …

Modeling social systems and studying their dynamical behavior plays an important role in
many fields of research. Agent-based modeling provides a high degree of detail into artificial …

The current healthcare industry in the United States of America is heavily invested in data
analytics to help manage complex business challenges. The problem is that business …

Poincaré's geometric representation has long been fundamental in dynamical system
analysis. However, its limitations in handling high-dimensional and uncertain systems have …

Understanding human decision-making in complex systems, such as supply chains, is a
challenging yet crucial task. Although various fields and disciplines, including psychology …