Seamus Hill is a member of the Computational Intelligence Research Group at NUIG.  He researches in the areas of Evolutionary Computation and Evolutionary game theory and is willing to discuss potential project supervision in any of those domains.  Further information on his research is available at and

Detecting Structures in Complex Social Networks using Evolutionary Algorithms

Being able to detect structures in complex social networks, such as cliques on Twitter graphs, is critical as it allows the ability to locate and identify links between structures and functions. By identifying various communities we can provide information as to how the network functions and the impact of topologies. There are a number of different approaches used in the detection of structures and this research focuses on the use of evolutionary algorithms to identify various communities.

Examining the use of Evolutionary Algorithms in Evolutionary Game Theory

Evolutionary game theory (EGT) is the application of game theory to evolving populations on artificial life organisms. EGT allows the researcher to examine dynamic games, which are centered, not by the idea of rational players, but on the population dynamics. This project examines the use of evolutionary algorithms and their representations in the study of population dynamics. The project examines the effects of altering the representation of the evolutionary algorithm to introduce a number of biological concepts and to analyse the impact of a multi-layered representation on population dynamics.