Resilience in aging through complexity and creative industry

Project granted in NWO’s Complexity and Creative Industry call: Grip on Transitions and Resilience. 2 PhD’s and 1 Postdoc will soon be hired.

Risk Factor Evolution for Counterparty Credit Risk under a Hidden Markov Model

The proposed HMM2 method predicts extreme situations better than the classic method.

Semi-intrusive Uncertainty Propagation for multiscale models

Anna Nikishova and Alfons G. Hoekstra have published an article on semi-intrusive Uncertainty Propagation for multiscale models in the Journal of Computational Science

Morphogenesis in Robotic Swarms

New results about bio-inspired technics applied in robotics, published in Science Robotics.

Inferring causation from time series in Earth system sciences

A perspective article in Nature Communications on causality inference techniques specifically for climate sciences

Group Mission

We live in a highly connected and strongly coupled world, and are surrounded by a large diversity of complex systems. All these systems have one thing in common: they process information. We aim to understand this information processing in such dynamic multi-level complex systems.

Can we detect and describe the computational structure in dynamic processes and can we provide a quantitative characterization of essential aspects of this structure? When modeling for instance traffic in a city, the interactions between the individuals driving the cars, the bicycles, and pedestrians result in a dynamic self-organizing interaction structure, which is superimposed on the road network. This can be seen as a dynamical computational structure where information is exchanged, stored, and processed. What are the essential aspects of this structure, and how do they determine the way in which information is actually stored, transferred, and processed in complex systems? And what does that mean for the overall system behavior, that is, for their emergent properties? Can we then better understand emergent properties and critical phenomena such as tipping points? For instance, where do traffic jams come from, which all of sudden seem to appear from thin air? Or, can we get a deeper understanding of the systemic economic crises that struck us in 2008? Are we able to steer or control such emergent properties? What can we do to prevent traffic jams while maintaining the throughput on the road? Maybe by bringing down velocity, or slightly controlling the traffic entering a road on the individual car level? Or more dramatically, can we ‘nudge’ the behavior of countries, large companies, and/or individuals to fight the climate change? The ever increasing and abundant availability of data, both from science and society, drives our research. We study complex systems in the context of methods like multi-scale cellular automata, dynamic networks and individual agent based models. The challenges include data-driven modeling of multi-level systems and their dynamics as well as conceptual, theoretical and methodological foundations that are necessary to understand these processes and the associated predictability limits of such large-scale computer simulations.

“Nature is a Complex System that processes information. Computational Science aims to make the complexity of those systems tractable.”

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Twitter Feed (@UvA_CSL)

Identity is crucial to understand internal migration. Our new paper is out!
#Migration #Netherlands #fractal #identity @RickQuax @UvA_CSL @Urbansci_MDPI

We are proud to announce MUSCLE 3 release 0.1.0! MUSCLE 3 is a brand new implementation of the MUltiscale Coupling Library and Environment, with new features and more ease-of-use. See to get started! Brought to you by @UvA_CSL and @eScienceCenter.

Our article with @alfonshoekstra from @UvA_CSL and @VECMA4 on the semi-intrusive #Uncertainty Propagation methods is online: Here we discuss an efficient way to estimate uncertainty in the output of #multiscale models using their coupling structure. #UQ

Great work by our lab's very own Jaap Kaandorp!

Indeed, let's 'causify' the field! 🙂 And a big thank you to @jakob_runge and others, was a joy!

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