Sociogenesis in unbounded space: modelling self-organised cohesive collective motion

Zohar Neu, Luca Giuggioli

Research output: Contribution to journalArticle (Academic Journal)peer-review

Abstract

Maintaining cohesion between randomly moving agents in unbounded space is an essential functionality for many real-world applications requiring distributed multi-agent systems. We develop a bio-inspired collective movement model in 1D unbounded space to ensure such functionality. Using an internal agent belief to estimate the mesoscopic state of the system, agent motion is coupled to a dynamically self-generated social ranking variable. This coupling between social information and individual movement is exploited to induce spatial self-sorting and produces an adaptive, group-relative coordinate system that stabilises random motion in unbounded space. We investigate the state-space of the model in terms of its key control parameters and find two separate regimes for the system to attain dynamical cohesive states, including a Partial Sensing regime in which the system self-selects nearest-neighbour distances so as to ensure a near-constant mean number of sensed neighbours. Overall, our approach constitutes a novel theoretical development in models of collective movement, as it considers agents who make decisions based on internal representations of their social environment that explicitly take into account spatial variation in a dynamic internal variable.

Original languageEnglish
Article number035002
Number of pages8
JournalPhysical Biology
Volume20
Issue number3
DOIs
Publication statusPublished - 28 Mar 2023

Bibliographical note

Funding Information:
This work was carried out using the computational facilities of the Advanced Computing Research Centre, University of Bristol. We acknowledge funding of an Amazon Research Award to L G. L G also acknowledges funding from BBSRC Grant No. BB/T012196/1 and NERC Grant No. NE/W00545X/1.

Publisher Copyright:
© 2023 The Author(s). Published by IOP Publishing Ltd.

Structured keywords

  • Engineering Mathematics Research Group

Keywords

  • Animals
  • Behavior, Animal
  • Motion
  • Movement

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