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Dynamical analysis of evolutionary public goods game on signed networks.
Zhong, Xiaowen; Huang, Guo; Wang, Ningning; Fan, Ying; Di, Zengru.
Afiliação
  • Zhong X; School of Systems Science, Beijing Normal University, 100875 Beijing, China.
  • Huang G; School of Systems Science, Beijing Normal University, 100875 Beijing, China.
  • Wang N; School of Systems Science, Beijing Normal University, 100875 Beijing, China.
  • Fan Y; School of Systems Science, Beijing Normal University, 100875 Beijing, China.
  • Di Z; School of Systems Science, Beijing Normal University, 100875 Beijing, China.
Chaos ; 32(2): 023107, 2022 Feb.
Article em En | MEDLINE | ID: mdl-35232045
In evolutionary dynamics, the population structure and multiplayer interactions significantly impact the evolution of cooperation levels. Previous works mainly focus on the theoretical analysis of multiplayer games on regular networks or pairwise games on complex networks. Combining these two factors, complex networks and multiplayer games, we obtain the fixation probability and fixation time of the evolutionary public goods game in a structured population represented by a signed network. We devise a stochastic framework for estimating fixation probability with weak mistrust or strong mistrust mechanisms and develop a deterministic replicator equation to predict the expected density of cooperators when the system evolves to the equilibrium on a signed network. Specifically, the most interesting result is that negative edges diversify the cooperation steady state, evolving in three different patterns of fixed probability in Erdös-Rényi signed and Watts-Strogatz signed networks with the new "strong mistrust" mechanism.
Assuntos

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Evolução Biológica / Teoria dos Jogos Tipo de estudo: Prognostic_studies Idioma: En Revista: Chaos Assunto da revista: CIENCIA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Evolução Biológica / Teoria dos Jogos Tipo de estudo: Prognostic_studies Idioma: En Revista: Chaos Assunto da revista: CIENCIA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China