Rewarding evolutionary fitness with links between populations promotes cooperation

Zhen Wang, Attila Szolnoki, Matjaž Perc

Research output: Contribution to journalArticle

149 Citations (Scopus)

Abstract

Evolution of cooperation in the prisoner[U+05F3]s dilemma and the public goods game is studied, where initially players belong to two independent structured populations. Simultaneously with the strategy evolution, players whose current utility exceeds a threshold are rewarded by an external link to a player belonging to the other population. Yet as soon as the utility drops below the threshold, the external link is terminated. The rewarding of current evolutionary fitness thus introduces a time-varying interdependence between the two populations. We show that, regardless of the details of the evolutionary game and the interaction structure, the self-organization of fitness and reward gives rise to distinguished players that act as strong catalysts of cooperative behavior. However, there also exist critical utility thresholds beyond which distinguished players are no longer able to percolate. The interdependence between the two populations then vanishes, and cooperators are forced to rely on traditional network reciprocity alone. We thus demonstrate that a simple strategy-independent form of rewarding may significantly expand the scope of cooperation on structured populations. The formation of links outside the immediate community seems particularly applicable in human societies, where an individual is typically member in many different social networks.

Original languageEnglish
Pages (from-to)50-56
Number of pages7
JournalJournal of Theoretical Biology
Volume349
DOIs
Publication statusPublished - May 21 2014

Keywords

  • Coevolution
  • Evolutionary games
  • Interdependent networks
  • Reward
  • Self-organization

ASJC Scopus subject areas

  • Statistics and Probability
  • Modelling and Simulation
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

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