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Research

Foundations of complex systems

Exploring the dynamics of complex systems from a fundamental perspective is crucial for further reasoning about the effects of our intervention strategies on complex challenges, whether climate change, global health or financial markets. By using novel mathematical and computational methods, we aim to better understand and predict complex processes.

Complex adaptive systems can be defined as systems with many parts that interact (often non-linearly) to produce emerging behaviour that cannot easily be explained in terms of the individual constituent elements (e.g. ecosystems, brains, cities). Characteristics of complex systems, such as tipping points, emergence, intractability and resilience (to name a few examples) are found in many of today’s most pressing scientific and societal challenges. Exploring the dynamics of complex systems from a fundamental perspective is crucial for further reasoning about the effects of our intervention strategies, and the controllability of the system itself.

This research programme explores new ways to reason about complexity using information theory and statistical mechanics and experimental methods such as agent-based models and complex networks.

Scientific Lead

Peter Sloot

Professor of Complex Adaptive Systems, University of Amsterdam
Professor of Complex System Simulations, Nanyang Technological University

Peter Sloot

My research focuses on how nature processes information, using computational modelling and simulation as well as formal methods. This work can be applied to a large variety of applications, such as modelling the virology and epidemiology of infectious diseases (e.g. HIV). My theoretical work focuses on out-of-equilibrium dynamics of complex adaptive systems using information theory and thermodynamics.

 

Research Fellows

Ingrid van de Leemput

will study the dynamics of tipping elements in relation to full-system dynamics, with the ultimate goal to develop a generic approach to study subsystem and systemic resilience of complex systems.

Rick Quax

will work with several scientists on diverse complexity related questions to explore the utility of information theory applied to various domains.

More information

To find out more about this research theme, or discuss getting involved, contact Peter Sloot.

prof. dr. P.M.A. (Peter) Sloot

Faculty of Science

Informatics Institute