Networking effects on cooperation in evolutionary N-person threshold games

Weihao Wang, Benyun SHI*

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

Abstract

Evolutionary game theory has been extensively employed to study the evolution of cooperation in human society. Many previous studies have shown that public cooperation can emerge from positive interactions and social diversity in structured populations. Here we study the evolution of cooperation under N-person interactions, where a minimum threshold of individuals must cooperate to produce public benefits. This is a very common phenomenon in teamwork, especially given the limited capacity of individuals. In this paper, we first present two scenarios of individual contribution mechanisms under an N-person threshold game to characterize such real-world situations. Then, we analyze the stable equilibrium for both scenarios of threshold games in well-mixed populations. Finally, we carry out simulations on three types of complex networks to evaluate the effects of both individual interactions and social diversity on the evolution of cooperation in structured populations. The analytical and simulation results in this paper offer a new insight into the evolution of cooperation in the face of threshold.

Original languageEnglish
Title of host publication2017 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2017
PublisherIEEE
Pages209-214
Number of pages6
ISBN (Electronic)9781538630167
DOIs
Publication statusPublished - 27 Feb 2018
Event2017 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2017 - Shenzhen, China
Duration: 15 Dec 201717 Dec 2017

Publication series

Name2017 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2017
Volume2018-January

Conference

Conference2017 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2017
Country/TerritoryChina
CityShenzhen
Period15/12/1717/12/17

Scopus Subject Areas

  • Safety, Risk, Reliability and Quality
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications

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