Reputation-based investment helps to optimize group behaviors in spatial lattice networks

Hong Ding, Lin Cao, Yizhi Ren, Kim Kwang Raymond Choo, Benyun SHI

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

Encouraging cooperation among selfish individuals is crucial in many real-world systems, where individuals' collective behaviors can be analyzed using evolutionary public goods game. Along this line, extensive studies have shown that reputation is an effective mechanism to investigate the evolution of cooperation. In most existing studies, participating individuals in a public goods game are assumed to contribute unconditionally into the public pool, or they can choose partners based on a common reputation standard (e.g., preferences or characters). However, to assign one reputation standard for all individuals is impractical in many real-world deployment. In this paper, we introduce a reputation tolerance mechanism that allows an individual to select its potential partnersand decide whether or not to contribute an investment to the public pool based on its tolerance to other individuals' reputation. Specifically, an individual takes part in a public goods game only if the number of participants with higher reputation exceeds the value of its tolerance. Moreover, in this paper, an individual's reputation can increase or decrease in a bounded interval based on its historical behaviors.We explore the principle that how the reputation tolerance and conditional investment mechanisms can affect the evolution of cooperation in spatial lattice networks. Our simulation results demonstrate that a larger tolerance value can achieve an environment that promote the cooperation of participants.

Original languageEnglish
Article numbere0162781
JournalPLoS ONE
Volume11
Issue number9
DOIs
Publication statusPublished - Sep 2016

Scopus Subject Areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • General

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