CABDyN Complexity Centre
Our aim is to define shared research questions and transferable and generalisable methods and techniques which will enable a better understanding of the dynamic and functional properties of network structures encountered in different contexts and disciplines. This involves the development of new statistical measures to characterize network structures and properties, so that the key features of incompletely mapped or noisy empirical networks can be summarised efficiently. At the same time, we aim to elucidate the fundamental properties of different classes of parsimonious models in which agents are linked by non-trivial networks.
We hope that the combination of these two strands of research may provide a better understanding of how the microstates of a networked system map into the global system behaviour, how global network characteristics influence the microstates, and what role intermediate mesoscopic structures play. This should allow us to understand network dynamics at many different scales, and will help elucidate functional network properties such as efficiency, robustness, persistence etc.
We are committed to the development of tools and methods which enable the transfer of desirable properties from networks which have emerged and evolved in competitive environments, such as many biological and socio-economic systems, to designed networks, such as computer networks, supply chains or distributed organizations.