Refining self-propelled particle models for collective behaviour
Swarming, schooling, flocking and herding are all names given to the wide variety of collective behaviours exhibited by groups of animals, bacteria and even individual cells. More generally, the term swarming describes the behaviour of an aggregate of agents (not necessarily biological) of similar s...
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Format: | Journal article |
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Applied Mathematics Institute, University of Alberta
2010
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_version_ | 1797095307740184576 |
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author | Baker, R Yates, C Erban, R |
author_facet | Baker, R Yates, C Erban, R |
author_sort | Baker, R |
collection | OXFORD |
description | Swarming, schooling, flocking and herding are all names given to the wide variety of collective behaviours exhibited by groups of animals, bacteria and even individual cells. More generally, the term swarming describes the behaviour of an aggregate of agents (not necessarily biological) of similar size and shape which exhibit some emergent property such as directed migration or group cohesion. In this paper we review various individual-based models of collective behaviour and discuss their merits and drawbacks. We further analyse some one-dimensional models in the context of locust swarming. In specific models, in both one and two dimensions, we demonstrate how varying parameters relating to how much attention individuals pay to their neighbours can dramatically change the behaviour of the group. We also introduce leader individuals to these models. Leader individuals have the ability to guide the swarm to a greater or lesser degree as we vary the parameters of the model. Finally, we consider evolutionary scenarios for models with leaders in which individuals are allowed to evolve the degree of influence neighbouring individuals have on their subsequent motion. |
first_indexed | 2024-03-07T04:26:01Z |
format | Journal article |
id | oxford-uuid:cca4ab34-9b0a-464b-9027-7873678c9294 |
institution | University of Oxford |
last_indexed | 2024-03-07T04:26:01Z |
publishDate | 2010 |
publisher | Applied Mathematics Institute, University of Alberta |
record_format | dspace |
spelling | oxford-uuid:cca4ab34-9b0a-464b-9027-7873678c92942022-03-27T07:23:24ZRefining self-propelled particle models for collective behaviourJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:cca4ab34-9b0a-464b-9027-7873678c9294Symplectic Elements at OxfordApplied Mathematics Institute, University of Alberta2010Baker, RYates, CErban, RSwarming, schooling, flocking and herding are all names given to the wide variety of collective behaviours exhibited by groups of animals, bacteria and even individual cells. More generally, the term swarming describes the behaviour of an aggregate of agents (not necessarily biological) of similar size and shape which exhibit some emergent property such as directed migration or group cohesion. In this paper we review various individual-based models of collective behaviour and discuss their merits and drawbacks. We further analyse some one-dimensional models in the context of locust swarming. In specific models, in both one and two dimensions, we demonstrate how varying parameters relating to how much attention individuals pay to their neighbours can dramatically change the behaviour of the group. We also introduce leader individuals to these models. Leader individuals have the ability to guide the swarm to a greater or lesser degree as we vary the parameters of the model. Finally, we consider evolutionary scenarios for models with leaders in which individuals are allowed to evolve the degree of influence neighbouring individuals have on their subsequent motion. |
spellingShingle | Baker, R Yates, C Erban, R Refining self-propelled particle models for collective behaviour |
title | Refining self-propelled particle models for collective behaviour |
title_full | Refining self-propelled particle models for collective behaviour |
title_fullStr | Refining self-propelled particle models for collective behaviour |
title_full_unstemmed | Refining self-propelled particle models for collective behaviour |
title_short | Refining self-propelled particle models for collective behaviour |
title_sort | refining self propelled particle models for collective behaviour |
work_keys_str_mv | AT bakerr refiningselfpropelledparticlemodelsforcollectivebehaviour AT yatesc refiningselfpropelledparticlemodelsforcollectivebehaviour AT erbanr refiningselfpropelledparticlemodelsforcollectivebehaviour |