Getting a grip on complex systems
The Institute for Complex Molecular Systems (ICMS) of the Eindhoven University of Technology (TU/e) is happy to invite you to a one-day symposium entitled, Getting a grip on complex systems. This event will be organized on November 8, 2023, in Ceres 0.31 at TU/e.
Please register via this link before October 31st.
The goal of this event is to highlight recent advances in complex networked systems from both the Network Science and the Dynamics and Control perspective, to highlight relevant research topics in both domains, identify common challenges and to foster collaborations. The focus area Grip on Complexity of the Institute for Complex Molecular Systems (ICMS) at the Eindhoven University of Technology (TU/e) aims at fundamental understanding of complex networked systems from two important complementary points of view: Network Science, and Dynamics and Control. In Network Science, networks are typically complex and the dynamics relatively simple, while in Dynamical Systems & Control, the dynamics is typically complex, while the networks are relatively simple. Thus, building bridges between these areas will enhance and advance the study of complex dynamics on complex networks.
Complex networked systems consist of many components that are all connected to each other. Although these mutual interactions are often simple and predictable, on the scale of the entire system emergent and unpredictable behavior arises. Due to external influences, a complex system, sometimes quite suddenly, can also become “completely new”. Complex networked systems are all around us: big ones, such as the climate, the Internet and the global economy, and smaller ones, such as local transport networks, traffic and our own body and brain.
The complexity of such systems lies both in their complex infrastructure (the network) and the highly interconnected processes that happen on it. These two levels require different techniques for modeling, network science for the infrastructure and dynamics and control theory for the processes. The combination of these two approaches provides a better understanding of the complex system. Understanding this complexity can teach us to recognize earlier turning points in complex systems and to influence and control undesired behavior in clever ways; here one may recognize the ubiquitous ‘analysis and synthesis’ question in complexity science. It also will enable us to design complex networked systems with extremely useful applications, such as smarter materials or stable power networks with thousands of small and volatile producers.