research
Here we describe our main areas of interest. For more details on the ongoing research, please refer to the publications page.
Artificial Life and Game Theory
Study of the effects of combining forms of learning. Analysis of classes of strategies in a range of domains, with recent work focussing on the impact of social structures on the emergence of cooperation.
Evolutionary computation and applications
We have been applying evolutionary computation techniques to solve problems in a wide range of domains, including graph generation, swarm robotics and evolutionary art and design.
Information retrieval
Combining sources of evidence, learning approaches (applied to weighting schemes, feedback and proximity information), user modelling.
Recommendation and collaborative filtering
Recommendation tools are now a common component in many online sites which involve a user choosing to view or purchase items based on personal preferences. We have been researching a range of approaches and techniques in the analysis of the usefulness and novelty of recommendations and many others.