title: Adaptive network models of collective decision making in swarming systems.
abstract: We consider a class of adaptive network models where links can only be created or deleted between nodes in different states. These models provide an approximate description of a set of systems where nodes represent agents moving in physical or abstract space, the state of each node represents the agent's heading direction, and links indicate mutual awareness. We show analytically that the adaptive network description captures a phase transition to collective motion in some swarming systems, such as the Vicsek model, and that the properties of this transition are determined by the number of states (discrete heading directions) that can be accessed by each agent.
authors.affiliation: Max Planck Institute for the Physics of Complex Systems, 01187 Dresden, Germay.
authors.forename: Li
authors.initials: L
authors.lastname: Chen
authors.affiliation: CHuepe Labs, 922 W 18th Place, Chicago, Illinois 60608, USA and Northwestern Institute on Complex Systems, Northwestern University, Evanston, Illinois 60208, USA.
authors.forename: Cristián
authors.initials: C
authors.lastname: Huepe
authors.affiliation: Department of Engineering Mathematics, Merchant Venturers Building, University of Bristol, Woodland Road, Clifton, Bristol BS8 ITR, United Kingdom.
authors.forename: Thilo
authors.initials: T
authors.lastname: Gross
mesh_terms: D003657:Decision Making; D008954:Models, Biological; D009038:Motion; D044367:Phase Transition