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Personal sustained cooperation based on networked evolutionary game theory
Evolutionary game theory on complex networks provides an effective theoretical tool to explain the emergence of sustained cooperative behavior. Human society has formed various organizational networks. The network structure and individual behavior take on a variety of forms. This diversity provides...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10241875/ https://www.ncbi.nlm.nih.gov/pubmed/37277442 http://dx.doi.org/10.1038/s41598-023-36318-7 |
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author | Yan, Jun |
author_facet | Yan, Jun |
author_sort | Yan, Jun |
collection | PubMed |
description | Evolutionary game theory on complex networks provides an effective theoretical tool to explain the emergence of sustained cooperative behavior. Human society has formed various organizational networks. The network structure and individual behavior take on a variety of forms. This diversity provides the basis for choice, so it is crucial for the emergence of cooperation. This article provides a dynamic algorithm for individual network evolution, and calculates the importance of different nodes in the network evolution process. In the dynamic evolution simulation, the probability of the cooperation strategy and betrayal strategy is described. In the individual interaction network, cooperative behavior will promote the continuous evolution of individual relationships and form a better aggregative interpersonal network. The interpersonal network of betrayal has been in a relatively loose state, and its continuity must rely on the participation of new nodes, but there will be certain "weak links" in the existing nodes of the network. |
format | Online Article Text |
id | pubmed-10241875 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-102418752023-06-07 Personal sustained cooperation based on networked evolutionary game theory Yan, Jun Sci Rep Article Evolutionary game theory on complex networks provides an effective theoretical tool to explain the emergence of sustained cooperative behavior. Human society has formed various organizational networks. The network structure and individual behavior take on a variety of forms. This diversity provides the basis for choice, so it is crucial for the emergence of cooperation. This article provides a dynamic algorithm for individual network evolution, and calculates the importance of different nodes in the network evolution process. In the dynamic evolution simulation, the probability of the cooperation strategy and betrayal strategy is described. In the individual interaction network, cooperative behavior will promote the continuous evolution of individual relationships and form a better aggregative interpersonal network. The interpersonal network of betrayal has been in a relatively loose state, and its continuity must rely on the participation of new nodes, but there will be certain "weak links" in the existing nodes of the network. Nature Publishing Group UK 2023-06-05 /pmc/articles/PMC10241875/ /pubmed/37277442 http://dx.doi.org/10.1038/s41598-023-36318-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Yan, Jun Personal sustained cooperation based on networked evolutionary game theory |
title | Personal sustained cooperation based on networked evolutionary game theory |
title_full | Personal sustained cooperation based on networked evolutionary game theory |
title_fullStr | Personal sustained cooperation based on networked evolutionary game theory |
title_full_unstemmed | Personal sustained cooperation based on networked evolutionary game theory |
title_short | Personal sustained cooperation based on networked evolutionary game theory |
title_sort | personal sustained cooperation based on networked evolutionary game theory |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10241875/ https://www.ncbi.nlm.nih.gov/pubmed/37277442 http://dx.doi.org/10.1038/s41598-023-36318-7 |
work_keys_str_mv | AT yanjun personalsustainedcooperationbasedonnetworkedevolutionarygametheory |