Multiscale Modelling Tool: Mathematical modelling of collective behaviour without the maths.

Collective behaviour is of fundamental importance in the life sciences, where it appears at levels of biological complexity from single cells to superorganisms, in demography and the social sciences, where it describes the behaviour of populations, and in the physical and engineering sciences, where...

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Main Authors: James A R Marshall, Andreagiovanni Reina, Thomas Bose
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2019-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0222906
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spelling doaj-46eeeea6049845b2b8fe7c7a82a676a22021-03-03T21:10:10ZengPublic Library of Science (PLoS)PLoS ONE1932-62032019-01-01149e022290610.1371/journal.pone.0222906Multiscale Modelling Tool: Mathematical modelling of collective behaviour without the maths.James A R MarshallAndreagiovanni ReinaThomas BoseCollective behaviour is of fundamental importance in the life sciences, where it appears at levels of biological complexity from single cells to superorganisms, in demography and the social sciences, where it describes the behaviour of populations, and in the physical and engineering sciences, where it describes physical phenomena and can be used to design distributed systems. Reasoning about collective behaviour is inherently difficult, as the non-linear interactions between individuals give rise to complex emergent dynamics. Mathematical techniques have been developed to analyse systematically collective behaviour in such systems, yet these frequently require extensive formal training and technical ability to apply. Even for those with the requisite training and ability, analysis using these techniques can be laborious, time-consuming and error-prone. Together these difficulties raise a barrier-to-entry for practitioners wishing to analyse models of collective behaviour. However, rigorous modelling of collective behaviour is required to make progress in understanding and applying it. Here we present an accessible tool which aims to automate the process of modelling and analysing collective behaviour, as far as possible. We focus our attention on the general class of systems described by reaction kinetics, involving interactions between components that change state as a result, as these are easily understood and extracted from data by natural, physical and social scientists, and correspond to algorithms for component-level controllers in engineering applications. By providing simple automated access to advanced mathematical techniques from statistical physics, nonlinear dynamical systems analysis, and computational simulation, we hope to advance standards in modelling collective behaviour. At the same time, by providing expert users with access to the results of automated analyses, sophisticated investigations that could take significant effort are substantially facilitated. Our tool can be accessed online without installing software, uses a simple programmatic interface, and provides interactive graphical plots for users to develop understanding of their models.https://doi.org/10.1371/journal.pone.0222906
collection DOAJ
language English
format Article
sources DOAJ
author James A R Marshall
Andreagiovanni Reina
Thomas Bose
spellingShingle James A R Marshall
Andreagiovanni Reina
Thomas Bose
Multiscale Modelling Tool: Mathematical modelling of collective behaviour without the maths.
PLoS ONE
author_facet James A R Marshall
Andreagiovanni Reina
Thomas Bose
author_sort James A R Marshall
title Multiscale Modelling Tool: Mathematical modelling of collective behaviour without the maths.
title_short Multiscale Modelling Tool: Mathematical modelling of collective behaviour without the maths.
title_full Multiscale Modelling Tool: Mathematical modelling of collective behaviour without the maths.
title_fullStr Multiscale Modelling Tool: Mathematical modelling of collective behaviour without the maths.
title_full_unstemmed Multiscale Modelling Tool: Mathematical modelling of collective behaviour without the maths.
title_sort multiscale modelling tool: mathematical modelling of collective behaviour without the maths.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2019-01-01
description Collective behaviour is of fundamental importance in the life sciences, where it appears at levels of biological complexity from single cells to superorganisms, in demography and the social sciences, where it describes the behaviour of populations, and in the physical and engineering sciences, where it describes physical phenomena and can be used to design distributed systems. Reasoning about collective behaviour is inherently difficult, as the non-linear interactions between individuals give rise to complex emergent dynamics. Mathematical techniques have been developed to analyse systematically collective behaviour in such systems, yet these frequently require extensive formal training and technical ability to apply. Even for those with the requisite training and ability, analysis using these techniques can be laborious, time-consuming and error-prone. Together these difficulties raise a barrier-to-entry for practitioners wishing to analyse models of collective behaviour. However, rigorous modelling of collective behaviour is required to make progress in understanding and applying it. Here we present an accessible tool which aims to automate the process of modelling and analysing collective behaviour, as far as possible. We focus our attention on the general class of systems described by reaction kinetics, involving interactions between components that change state as a result, as these are easily understood and extracted from data by natural, physical and social scientists, and correspond to algorithms for component-level controllers in engineering applications. By providing simple automated access to advanced mathematical techniques from statistical physics, nonlinear dynamical systems analysis, and computational simulation, we hope to advance standards in modelling collective behaviour. At the same time, by providing expert users with access to the results of automated analyses, sophisticated investigations that could take significant effort are substantially facilitated. Our tool can be accessed online without installing software, uses a simple programmatic interface, and provides interactive graphical plots for users to develop understanding of their models.
url https://doi.org/10.1371/journal.pone.0222906
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