Popularity enhances the interdependent network reciprocity
Interdependent networks (IN) are collections of non-trivially interrelated graphs that are not physically connected, and provide a more realistic representation of real-world networked systems as compared to traditional isolated networks. In particular, they are an efficient tool to study the evolut...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2018-01-01
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| Series: | New Journal of Physics |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1367-2630/aaf334 |
| _version_ | 1827873251613736960 |
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| author | Chen Liu Chen Shen Yini Geng Shudong Li Chengyi Xia Zhihong Tian Lei Shi Ruiwu Wang Stefano Boccaletti Zhen Wang |
| author_facet | Chen Liu Chen Shen Yini Geng Shudong Li Chengyi Xia Zhihong Tian Lei Shi Ruiwu Wang Stefano Boccaletti Zhen Wang |
| author_sort | Chen Liu |
| collection | DOAJ |
| description | Interdependent networks (IN) are collections of non-trivially interrelated graphs that are not physically connected, and provide a more realistic representation of real-world networked systems as compared to traditional isolated networks. In particular, they are an efficient tool to study the evolution of cooperative behavior from the viewpoint of statistical physics. Here, we consider a prisoner dilemma game taking place in IN, and introduce a simple rule for the calculation of fitness that incorporates individual popularity, which in its turn is represented by one parameter α . We show that interdependence between agents in different networks influences the cooperative behavior trait. Namely, intermediate α values guarantee an optimal environment for the evolution of cooperation, while too high or excessively low α values impede cooperation. These results originate from an enhanced synchronization of strategies in different networks, which is beneficial for the formation of giant cooperative clusters wherein cooperators are protected from exploitation by defectors. |
| first_indexed | 2024-03-12T16:34:37Z |
| format | Article |
| id | doaj.art-8df726a6abf74096abed5d7af497e4c9 |
| institution | Directory Open Access Journal |
| issn | 1367-2630 |
| language | English |
| last_indexed | 2024-03-12T16:34:37Z |
| publishDate | 2018-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | New Journal of Physics |
| spelling | doaj.art-8df726a6abf74096abed5d7af497e4c92023-08-08T14:55:56ZengIOP PublishingNew Journal of Physics1367-26302018-01-01201212301210.1088/1367-2630/aaf334Popularity enhances the interdependent network reciprocityChen Liu0Chen Shen1Yini Geng2Shudong Li3Chengyi Xia4Zhihong Tian5Lei Shi6Ruiwu Wang7Stefano Boccaletti8Zhen Wang9Center for Ecology and Environmental Sciences, Northwestern Polytechnical University , Xi’an, 710072 People's Republic of ChinaSchool of Statistics and Mathematics, Yunnan University of Finance and Economics , Kunming, 650221, People's Republic of ChinaSchool of Statistics and Mathematics, Yunnan University of Finance and Economics , Kunming, 650221, People's Republic of ChinaCyberspace Institute of Advanced Technology, Guangzhou University , Guangzhou, 510006, People's Republic of ChinaKey Laboratory of Computer Vision and System and Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology , Tianjin, 300191, People's Republic of ChinaCyberspace Institute of Advanced Technology, Guangzhou University , Guangzhou, 510006, People's Republic of ChinaSchool of Statistics and Mathematics, Yunnan University of Finance and Economics , Kunming, 650221, People's Republic of ChinaCenter for Ecology and Environmental Sciences, Northwestern Polytechnical University , Xi’an, 710072 People's Republic of ChinaCNR, Institute of Complex Systems , Via Madonna del Piano, 10, I-50019, Sesto Fiorentino (FI), Italy; Unmanned Systems Research Institute, Northwestern Polytechnical University , Xi’an, 710072, People's Republic of ChinaSchool of Mechanical Engineering and Center for OPTical IMagery Analysis and Learning (OPTIMAL), Northwestern Polytechnical University , Xi’an, 710072, People's Republic of ChinaInterdependent networks (IN) are collections of non-trivially interrelated graphs that are not physically connected, and provide a more realistic representation of real-world networked systems as compared to traditional isolated networks. In particular, they are an efficient tool to study the evolution of cooperative behavior from the viewpoint of statistical physics. Here, we consider a prisoner dilemma game taking place in IN, and introduce a simple rule for the calculation of fitness that incorporates individual popularity, which in its turn is represented by one parameter α . We show that interdependence between agents in different networks influences the cooperative behavior trait. Namely, intermediate α values guarantee an optimal environment for the evolution of cooperation, while too high or excessively low α values impede cooperation. These results originate from an enhanced synchronization of strategies in different networks, which is beneficial for the formation of giant cooperative clusters wherein cooperators are protected from exploitation by defectors.https://doi.org/10.1088/1367-2630/aaf334interdependent networkscooperationevolutionary gamessynchronizaton |
| spellingShingle | Chen Liu Chen Shen Yini Geng Shudong Li Chengyi Xia Zhihong Tian Lei Shi Ruiwu Wang Stefano Boccaletti Zhen Wang Popularity enhances the interdependent network reciprocity New Journal of Physics interdependent networks cooperation evolutionary games synchronizaton |
| title | Popularity enhances the interdependent network reciprocity |
| title_full | Popularity enhances the interdependent network reciprocity |
| title_fullStr | Popularity enhances the interdependent network reciprocity |
| title_full_unstemmed | Popularity enhances the interdependent network reciprocity |
| title_short | Popularity enhances the interdependent network reciprocity |
| title_sort | popularity enhances the interdependent network reciprocity |
| topic | interdependent networks cooperation evolutionary games synchronizaton |
| url | https://doi.org/10.1088/1367-2630/aaf334 |
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