Adaptive network models of collective decision making in swarming systems.

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.

• Publication year

  2015

• Venue

  Physical Review E

• Publication date

  2015-07-29

• Fields of study

  Mathematics, Physics, Computer Science, Medicine

• Identifiers
  DOI 10.1103/PhysRevE.94.022415arXiv 1507.08100PMID 27627342
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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