We are in control of unprecedented amounts of data and computational power – yet we struggle to predict the severity of the next flu season, anticipate social unrest, assess the resilience of our democracies, or even forecast the traffic tonight. The bottleneck is neither technology nor data; it’s understanding complexity.
To address these challenges, a fundamental understanding of the foundations of complex systems is necessary.
It is necessary to uncover the principles that govern interconnected, evolutionary, dynamic systems before truly informed decisions become possible.
WHY IT'S COMPLEX
Complex systems such as supply chain networks, financial markets, or entire societies, are – to this day – so poorly understood because the components of these systems interact through networks and give rise to collective, emergent properties that have so far been difficult to explain and predict.
In complex systems, there is no representative element, no typical individual; moreover, a component’s structural position within a network is often more important than its size, and not everything is connected to everything else.
With the help of complexity science, the elements of a system – such as people, companies, and institutions in an economy – and the connections between them become visible for the first time, allowing the right measures to be derived.
OUR APPROACH
Explore the Research Topic ‘Foundations of Complex Systems’ – with all publications, stories, projects and visualizations.
In this research topic, multiple disciplines such as statistical physics, mathematical modeling, computational physics, agent-based modeling, data science, statistics, and sociology come together to establish the foundations for all other research areas, which build on the combination of theoretical modeling and empirical validation using real-world data.
Science, in the natural-science sense, means that hypotheses can be tested.
Complexity science, as a comparatively young discipline, was for many years largely limited to conceptual and theoretical work; only with the availability of large-scale datasets did these concepts become verifiable – with data.
This requires moving beyond the classical approach of pure aggregation and reduction, because in complex systems a small number of critical connections can be decisive. By combining physics-inspired models, mathematical theory, and empirical data, researchers can systematically investigate tipping points, phase transitions, and abrupt shifts in complex systems.
A Visual Explainer for Understanding Agent-Based Modeling
THE IMPACT
By overcoming rigid disciplinary boundaries, abstract mathematics becomes a universal analytical tool for real-world systems, making them, in the best sense, something that can be intuitively grasped and deeply understood.
Our world is not merely the sum of its parts, but the sum of its parts plus connections and networks – an understanding that is essential for addressing the most pressing challenges of our time.
The “Foundations of Complex Systems” research area provides the methodological basis for digital twins of complex systems that can accurately represent reality, making it possible – almost like watching a film – to see how systems behave and evolve, and ultimately to support better decisions based on transparent, interpretable models.
