Adaptive network models of collective decision making in swarming systems

Chen, Li; Huepe, Cristian; Gross, Thilo

doi:10.1103/PhysRevE.94.022415

Item

ITEM ACTIONSEXPORT

Add to Basket

Local TagsRelease HistoryDetailsSummary

Released

Journal Article

Adaptive network models of collective decision making in swarming systems

MPS-Authors

/persons/resource/persons184412

Chen, Li
Max Planck Institute for the Physics of Complex Systems, Max Planck Society;

External Resource

https://journals.aps.org/pre/abstract/10.1103/PhysRevE.94.022415
(Publisher version)

Fulltext (restricted access)

There are currently no full texts shared for your IP range.

Fulltext (public)

There are no public fulltexts stored in PuRe

Supplementary Material (public)

There is no public supplementary material available

Citation

Chen, L., Huepe, C., & Gross, T. (2016). Adaptive network models of collective decision making in swarming systems. Physical Review E, 94(2): 022415. doi:10.1103/PhysRevE.94.022415.

Cite as: https://hdl.handle.net/11858/00-001M-0000-002B-503D-E

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.