Modelling and simulation of self-organised behaviour in biological and bio-inspired systems

From molecular pathways to social groups, self-organisation is widely used in nature for flexible adaptive
control. It also has many engineering applications from nano-technology to telecommunications and robotics.
Yet, our understanding of how macro-level characteristics emerge from micro-level properties is very limited,
partly because no general modelling methods are available. We will develop stochastic modelling methods
and high-performance simulation techniques to bridge between micro and macro level. This will give
researchers in biology and a range of other disciplines powerful tools to explain and analyse complex selforganised
behaviour, and it will significantly increase our capacity to engineer reliable bio-inspired systems.