Adaptive network models of collective decision making in swarming systems

Li Chen, Cristián Huepe, Thilo Gross

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


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.

Original languageEnglish (US)
Article number022415
JournalPhysical Review E
Issue number2
StatePublished - Aug 18 2016

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Statistical and Nonlinear Physics
  • Statistics and Probability


Dive into the research topics of 'Adaptive network models of collective decision making in swarming systems'. Together they form a unique fingerprint.

Cite this