Collective animal behaviour and artificial swarm systems

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Early models of collective animal behaviour and many artificial swarm systems assume individuals and agents to be identical. Recent advances in animal behaviour observations show high individual heterogeneity in almost every collective animal behaviour system they study, and this heterogeneity is important for animal group structure and functioning. This PhD project will use unique datasets on the collective behaviour of fish shoals, bird flocks, and mammal groups, to address the mismatch between swarm model assumptions and reality. The aim of this PhD project is to understand heterogeneity's role in the emergence of collective patterns, with a view to engineering better artificial swarm systems.