Coevolutionary, coexisting learning and teaching agents model for prisoner's dilemma games enhancing cooperation with assortative heterogeneous networks

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19 Citations (Scopus)

Abstract

Unlike other natural network systems, assortativity can be observed in most human social networks, although it has been reported that a social dilemma situation represented by the prisoner's dilemma favors dissortativity to enhance cooperation. We established a new coevolutionary model for both agents' strategy and network topology, where teaching and learning agents coexist. Remarkably, this model enables agents' enhancing cooperation more than a learners-only model on a time-frozen scale-free network and produces an underlying assortative network with a fair degree of power-law distribution. The model may imply how and why assortative networks are adaptive in human society.

Original languageEnglish
Pages (from-to)2955-2964
Number of pages10
JournalPhysica A: Statistical Mechanics and its Applications
Volume392
Issue number13
DOIs
Publication statusPublished - Jul 1 2013

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Condensed Matter Physics

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