Hierarchical self-organization of non-cooperating individuals.

Hierarchy is one of the most conspicuous features of numerous natural, technological and social systems. The underlying structures are typically complex and their most relevant organizational principle is the ordering of the ties among the units they are made of according to a network displaying hie...

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Autores principales:	Tamás Nepusz, Tamás Vicsek
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/0ab7626661ba451987d8b518c8ef8402
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spelling	oai:doaj.org-article:0ab7626661ba451987d8b518c8ef84022021-11-18T08:42:31ZHierarchical self-organization of non-cooperating individuals.1932-620310.1371/journal.pone.0081449https://doaj.org/article/0ab7626661ba451987d8b518c8ef84022013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24349070/?tool=EBIhttps://doaj.org/toc/1932-6203Hierarchy is one of the most conspicuous features of numerous natural, technological and social systems. The underlying structures are typically complex and their most relevant organizational principle is the ordering of the ties among the units they are made of according to a network displaying hierarchical features. In spite of the abundant presence of hierarchy no quantitative theoretical interpretation of the origins of a multi-level, knowledge-based social network exists. Here we introduce an approach which is capable of reproducing the emergence of a multi-levelled network structure based on the plausible assumption that the individuals (representing the nodes of the network) can make the right estimate about the state of their changing environment to a varying degree. Our model accounts for a fundamental feature of knowledge-based organizations: the less capable individuals tend to follow those who are better at solving the problems they all face. We find that relatively simple rules lead to hierarchical self-organization and the specific structures we obtain possess the two, perhaps most important features of complex systems: a simultaneous presence of adaptability and stability. In addition, the performance (success score) of the emerging networks is significantly higher than the average expected score of the individuals without letting them copy the decisions of the others. The results of our calculations are in agreement with a related experiment and can be useful from the point of designing the optimal conditions for constructing a given complex social structure as well as understanding the hierarchical organization of such biological structures of major importance as the regulatory pathways or the dynamics of neural networks.Tamás NepuszTamás VicsekPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 12, p e81449 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Tamás Nepusz Tamás Vicsek Hierarchical self-organization of non-cooperating individuals.
description	Hierarchy is one of the most conspicuous features of numerous natural, technological and social systems. The underlying structures are typically complex and their most relevant organizational principle is the ordering of the ties among the units they are made of according to a network displaying hierarchical features. In spite of the abundant presence of hierarchy no quantitative theoretical interpretation of the origins of a multi-level, knowledge-based social network exists. Here we introduce an approach which is capable of reproducing the emergence of a multi-levelled network structure based on the plausible assumption that the individuals (representing the nodes of the network) can make the right estimate about the state of their changing environment to a varying degree. Our model accounts for a fundamental feature of knowledge-based organizations: the less capable individuals tend to follow those who are better at solving the problems they all face. We find that relatively simple rules lead to hierarchical self-organization and the specific structures we obtain possess the two, perhaps most important features of complex systems: a simultaneous presence of adaptability and stability. In addition, the performance (success score) of the emerging networks is significantly higher than the average expected score of the individuals without letting them copy the decisions of the others. The results of our calculations are in agreement with a related experiment and can be useful from the point of designing the optimal conditions for constructing a given complex social structure as well as understanding the hierarchical organization of such biological structures of major importance as the regulatory pathways or the dynamics of neural networks.
format	article
author	Tamás Nepusz Tamás Vicsek
author_facet	Tamás Nepusz Tamás Vicsek
author_sort	Tamás Nepusz
title	Hierarchical self-organization of non-cooperating individuals.
title_short	Hierarchical self-organization of non-cooperating individuals.
title_full	Hierarchical self-organization of non-cooperating individuals.
title_fullStr	Hierarchical self-organization of non-cooperating individuals.
title_full_unstemmed	Hierarchical self-organization of non-cooperating individuals.
title_sort	hierarchical self-organization of non-cooperating individuals.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/0ab7626661ba451987d8b518c8ef8402
work_keys_str_mv	AT tamasnepusz hierarchicalselforganizationofnoncooperatingindividuals AT tamasvicsek hierarchicalselforganizationofnoncooperatingindividuals
_version_	1718421425604263936

Hierarchical self-organization of non-cooperating individuals.

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