Complex Systems Modeling Lab

At the dawn of this twenty-first century, the physicist Stephen Hawking remarked: "I think the next century will be the century of complexity." What an understatement! The term "complexity" is now used, and too often misused, in every day parlance. Complexity, it would appear, is everywhere.

Complexity, as a subject of research in this laboratory, refers to the nature and behavior of systems--objects consisting of many interacting components--that satisfy specific criteria. In doing so, complex systems can be distinguished from merely complicated systems. Borrowing from J.M. Ottino, a complicated system may consist of many interacting components yet not be complex in nature or behavior.

Specifically, a complex system is nonlinear, that is, the macro-scale behavior of a complex system is not merely the linear sum of the individual component behaviors. Complex systems are also said to be non-equilibrium--that is, they will be found in probabilistically unlikely states. They are also non-stationary in that they change in unpredictable ways over time. And lastly, they typically lack a single common scale displaying the same structure at multiple, hierarchical scales--in other words they are self-similar at different scales. Less technically, complex systems have the potential to produce emergent outcomes--truly surprising, unpredictable behaviors.

In the CSML, we are deeply interested in modeling complex systems in many domains--physical, environmental, social, healthcare, finance, and organization--to better understand their behavior. In this pursuit, we employ appropriate tools of investigation including large-scale simulation models, network analysis, and the use of high-performance computing platforms. Through our collective efforts, we seek to advance the art and practice of complex systems modeling.

Taming Complexity

The science of networks is experiencing a boom. But despite the necessary multidisciplinary approach to tackle the theory of complexity, scientists remain largely compartmentalized in their separate disciplines. Can they find a common voice?

Read the article here:



How Complexity Leads to Simplicity

Ecologist and TED Fellow Eric Berlow studies ecology and networks, exposing the interconnectedness of our ecosystems with climate change, government, corporations and more. Berlow doesn't feel overwhelmed when faced with complex systems. He knows that more information can lead to a better, simpler solution. Illustrating the tips and tricks for breaking down big issues, he distills an overwhelming infographic on U.S. strategy in Afghanistan to a few elementary points.

Watch the TED Talk here:


Big ideas, big data, big computing. Grand ambition? Is it too grand?

FuturICT wants science to catch up with the speed at which new problems and opportunities are arising in our changing world as consequences of globalization, technological, demographic and environmental change, and make a contribution to strengthening our societies' adaptiveness, resilience, and sustainability.

It will do so by developing new scientific approaches and combining these with the best established methods in areas like multi-scale computer modeling, social supercomputing, large-scale data mining and participatory platforms.