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Measuring complexity in organisms and organizations

While there is no consensus about the definition of complexity, it is widely accepted that the ability to produce uncertainty is the most prominent characteristic of complex systems. We introduce new metrics that purport to quantify the complexity of living organisms and social organizations based o...

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Autores principales: Rebout, Nancy, Lone, Jean-Christophe, De Marco, Arianna, Cozzolino, Roberto, Lemasson, Alban, Thierry, Bernard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8074971/
https://www.ncbi.nlm.nih.gov/pubmed/33959307
http://dx.doi.org/10.1098/rsos.200895
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author Rebout, Nancy
Lone, Jean-Christophe
De Marco, Arianna
Cozzolino, Roberto
Lemasson, Alban
Thierry, Bernard
author_facet Rebout, Nancy
Lone, Jean-Christophe
De Marco, Arianna
Cozzolino, Roberto
Lemasson, Alban
Thierry, Bernard
author_sort Rebout, Nancy
collection PubMed
description While there is no consensus about the definition of complexity, it is widely accepted that the ability to produce uncertainty is the most prominent characteristic of complex systems. We introduce new metrics that purport to quantify the complexity of living organisms and social organizations based on their levels of uncertainty. We consider three major dimensions regarding complexity: diversity based on the number of system elements and the number of categories of these elements; flexibility which bears upon variations in the elements; and combinability which refers to the patterns of connection between elements. These three dimensions are quantified using Shannon's uncertainty formula, and they can be integrated to provide a tripartite complexity index. We provide a calculation example that illustrates the use of these indices for comparing the complexity of different social systems. These indices distinguish themselves by a theoretical basis grounded on the amount of uncertainty, and the requirement that several aspects of the systems be accounted for to compare their degree of complexity. We expect that these new complexity indices will encourage research programmes aiming to compare the complexity levels of systems belonging to different realms.
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spelling pubmed-80749712021-05-05 Measuring complexity in organisms and organizations Rebout, Nancy Lone, Jean-Christophe De Marco, Arianna Cozzolino, Roberto Lemasson, Alban Thierry, Bernard R Soc Open Sci Organismal and Evolutionary Biology While there is no consensus about the definition of complexity, it is widely accepted that the ability to produce uncertainty is the most prominent characteristic of complex systems. We introduce new metrics that purport to quantify the complexity of living organisms and social organizations based on their levels of uncertainty. We consider three major dimensions regarding complexity: diversity based on the number of system elements and the number of categories of these elements; flexibility which bears upon variations in the elements; and combinability which refers to the patterns of connection between elements. These three dimensions are quantified using Shannon's uncertainty formula, and they can be integrated to provide a tripartite complexity index. We provide a calculation example that illustrates the use of these indices for comparing the complexity of different social systems. These indices distinguish themselves by a theoretical basis grounded on the amount of uncertainty, and the requirement that several aspects of the systems be accounted for to compare their degree of complexity. We expect that these new complexity indices will encourage research programmes aiming to compare the complexity levels of systems belonging to different realms. The Royal Society 2021-03-17 /pmc/articles/PMC8074971/ /pubmed/33959307 http://dx.doi.org/10.1098/rsos.200895 Text en © 2021 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited.
spellingShingle Organismal and Evolutionary Biology
Rebout, Nancy
Lone, Jean-Christophe
De Marco, Arianna
Cozzolino, Roberto
Lemasson, Alban
Thierry, Bernard
Measuring complexity in organisms and organizations
title Measuring complexity in organisms and organizations
title_full Measuring complexity in organisms and organizations
title_fullStr Measuring complexity in organisms and organizations
title_full_unstemmed Measuring complexity in organisms and organizations
title_short Measuring complexity in organisms and organizations
title_sort measuring complexity in organisms and organizations
topic Organismal and Evolutionary Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8074971/
https://www.ncbi.nlm.nih.gov/pubmed/33959307
http://dx.doi.org/10.1098/rsos.200895
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