Lewis, Jason Moghal (2018) Topological models of swarming. PhD thesis, University of Warwick.

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Abstract

We study the collective behaviour of animal aggregations, swarming, using theoretical models of collective motion. Focusing on bird flocking, we aim to reproduce two main aspects of real world aggregations: cohesion and coalignment. Following the observation that interactions between birds in the flock does not have a characteristic length-scale, we concentrate on topological, metric-free models of collective motion. We propose and analyse three novel models of swarming: two based on topological interactions between particles, which define interacting neighbours based on Voronoi tessellation of the group of particles, and one which uses the visual field of the agent. We explore the problem of cohesion, bounding of topological flocks in free space, by introducing the mechanism of neighbour anticipation. This relies on going towards the inferred future position of an individuals neighbours and results in providing the bounding forces for the group. We also address the issue of unrealistic density distributions in existing metric-free models by introducing a homogeneous, tunable motional bias throughout the swarm. The proposed model produces swarms with density distributions corresponding to empirical data from flocks of Starlings. Furthermore, we show that for a group with a visual information input and individuals moving so as to seek marginal opacity that alignment and group cohesion can be induced without the need for explicit aligning interaction rules between group members. For each of the proposed models a comprehensive analysis of characteristics and behaviour under different parameter sets is performed.

Item Type:	Thesis (PhD)
Subjects:	Q Science > QC Physics Q Science > QL Zoology
Library of Congress Subject Headings (LCSH):	Starlings -- Swarming -- Mathematical models, Tessellations (Mathematics), Swarming (Zoology) -- Mathematical models
Official Date:	September 2018
Dates:	Date Event September 2018 UNSPECIFIED
Institution:	University of Warwick
Theses Department:	Centre for Complexity Science
Thesis Type:	PhD
Publication Status:	Unpublished
Supervisor(s)/Advisor:	Turner, Matthew S.
Format of File:	pdf
Extent:	viii, 103 leaves : illustrations, charts
Language:	eng

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