SWARM · Empirical analysis and theoretical modelling of self-organized collective behaviour in three-dimensions: from insect swarms and bird flocks to new schemes of distributed coordination

Animal groups represent paradigmatic cases of self-organized collective behaviour, where global coordination arises from local rules of interaction between individuals. A major issue, both for theoretical studies and technological applications, is to understand how self-organization emerges within a system with distributed intelligence.SWARM aims at providing new knowledge about self-organization and collective behaviour in 3D animal aggregations. To do that, SWARM will export concepts and methods from physics, and will integrate empirical work, data analysis and theoretical modelling. In particular, SWARM will:i) Perform field experiments on large insect swarms and bird flocks and retrieve individual 3D coordinates and trajectories.ii) Perform a statistical characterization of swarming/flocking behaviour; obtain information on the interactions between group members, and on the rules followed by individuals.iii) Develop empirically based models of 3D animal collective behaviour and design efficient, biologically inspired, algorithms of distributed coordination.