Title of article :
Coevolutionary, coexisting learning and teaching agents model for prisoner’s dilemma games enhancing cooperation with assortative heterogeneous networks
Author/Authors :
Tanimoto، نويسنده , , Jun، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2013
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.
Keywords :
Evolutionary game on network , Assortative coefficient , Prisoner’s dilemma game , Coevolution
Journal title :
Physica A Statistical Mechanics and its Applications
Journal title :
Physica A Statistical Mechanics and its Applications