English

Environmental path-entropy and collective motion

Statistical Mechanics 2023-04-21 v2 Multiagent Systems

Abstract

Inspired by the swarming or flocking of animal systems we study groups of agents moving in unbounded 2D space. Individual trajectories derive from a ``bottom-up'' principle: individuals reorient to maximise their future path entropy over environmental states. This can be seen as a proxy for keeping options open, a principle that may confer evolutionary fitness in an uncertain world. We find an ordered (co-aligned) state naturally emerges, as well as disordered states or rotating clusters; similar phenotypes are observed in birds, insects and fish, respectively. The ordered state exhibits an order-disorder transition under two forms of noise: (i) standard additive orientational noise, applied to the post-decision orientations (ii) ``cognitive'' noise, overlaid onto each individual's model of the future paths of other agents. Unusually, the order increases at low noise, before later decreasing through the order-disorder transition as the noise increases further.

Keywords

Cite

@article{arxiv.2303.17906,
  title  = {Environmental path-entropy and collective motion},
  author = {Harvey L. Devereux and Matthew S. Turner},
  journal= {arXiv preprint arXiv:2303.17906},
  year   = {2023}
}

Comments

Corrected bibliography (removing erroneous refs.), Published 19 April 2023 Phys. Rev. Lett

R2 v1 2026-06-28T09:42:44.444Z