Collective animal behaviour and artificial swarm systems

早期的动物集体行为模型和许多人工蜂群系统都假定个体和代理人是相同的。动物行为观察的最新进展表明，他们研究的几乎每个动物集体行为系统中都存在着高度的个体异质性，这种异质性对动物群体的结构和功能很重要。这个博士项目将使用关于鱼群、鸟群和哺乳动物群体集体行为的独特数据集，以解决群体模型假设与现实之间的不匹配。这个博士项目的目的是了解异质性在集体模式出现中的作用，以期设计出更好的人工蜂群系统。

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.