Title: Collective Decision Making: From Bees to Robots via Multiscale Modelling
Abstract: I will give an overview of my studies on collective decision making in distributed systems of the last seven years. Such systems, found in biology, sociology, and engineering, are composed of a large number of interacting individuals that coordinate in order to reach a consensus. The main phases of the collective decision making process consist of identifying the available options, estimating their quality, and selecting the best option or any of them. I will present the main results of my research in understanding and designing each of these phases. Collective systems are inherently difficult to analyse as the stochastic nonlinear interactions between individuals can give rise to complex emergent dynamics. Therefore, I employ a collection of advanced techniques, commonly defined as multiscale modelling. Relying on a set of methods, rather than a single one, gives the benefit of having complementary techniques addressing one another’s limitations. In fact, through multiscale modelling, it is possible to analyse the systems at various levels of complexity and detail, from macroscopic group-level dynamics to microscopic individual-level behaviour, and from noise-free deterministic models to stochastic spatial descriptions. I finally shed a light on the recently developed opensource software for automated multiscale modelling.