Modelling and Simulation of complex socio-technical systems today faces various challenges: on the one hand, collected data increases every day, giving us potential deeper insights in systems and their behaviour. To get out most of the knowledge, we need sophisticated methods in data mining, machine learning and deep learning algorithms. On the other hand complexity of the systems increases, as well as profoundness of research questions addressed by stakeholders. So we need modelling and simulation methods enabling to simulate heterogeneous, complex systems. For this track we are looking for new approaches to combine both sides, which makes development, construction, monitoring, analysis, prediction of such systems easier, faster, more reliable and – one of the most important things – comprehensible for decision makers and other stakeholders, therefore increasing the understanding of natural systems and the acceptance of complex man made systems.
For further information please contact Niki Popper.