MAGICS: Methodological Advancements for Generalizable Insights into Complex Systems

MAGICS aims to transform our understanding of complex, evolving systems by developing fundamentally new modeling approaches. 

While the combination of big data and machine learning initially promised breakthroughs in predicting system behavior - from global economic networks to regional population dynamics - current methods have fallen short of expectations. MAGICS seeks innovative solutions that can better handle the challenges of systems that constantly change, interact with their environment, and respond to continuous self-observation.

Successful projects will create new theoretical frameworks and analytical tools that can reliably predict system behavior using real-world data, moving beyond the limitations of current statistical approaches to capture the true complexity of dynamic, interconnected systems.