The investigation of complex networks is important in many areas of research including social networks, protein interaction networks, cognitive networks and evolutionary networks. Research on this topic has received a lot of attention in computer science, physics and biology over the last ten years or so. A key focus of research concerns the dynamic behaviour of such networks over time. Particular attention has been given to coevolutionary networks, where the attributes of nodes within the network and the structure of the network itself influence how each other changes over time.
The goal in this project is to implement simulations of these networks in order to gain new insights into their dynamics. Objectives of the research include investigating the behaviour associated with different types of network structure (including random networks), the influence of different updating rules for both the attributes and the network structure, and the robustness of the network’s behaviour to changes in its structure.
It is anticipated that the project will initially focus on networks to represent how people’s opinions can evolve with their social relationships. In this context, the conditions under which a consensus of opinion emerges would be considered. However, other types of networks could also be explored. The project will also require design and implementation of efficient algorithms, visualizations of the networks, and investigation of how parallel or distributing computing techniques can be utilized.
First Supervisor: Glass, DH Dr
Second Supervisor: Wang, HY Dr
Third Supervisor: McCartney, M Dr
Collaboration: This project does not involve collaboration with another establishment