Evolutionary prisoner's dilemma games on the network with punishment and opportunistic partner switching

Abstract

PACS 87.23.Ge -Dynamics of social systems PACS 87.23.Kg -Dynamics of evolution PACS 02.50.Le -Decision theory and game theory Abstract -Punishment and partner switching are two well-studied mechanisms that support the evolution of cooperation. Observation of human behaviour suggests that the extent to which punishment is adopted depends on the usage of alternative mechanisms, including partner switching. In this study, we investigate the combined effect of punishment and partner switching in evolutionary prisoner's dilemma games conducted on a network. In the model, agents are located on the network and participate in the prisoner's dilemma games with punishment. In addition, they can opportunistically switch interaction partners to improve their payoff. Our Monte Carlo simulation showed that a large frequency of punishers is required to suppress defectors when the frequency of partner switching is low. In contrast, cooperation is the most abundant strategy when the frequency of partner switching is high regardless of the strength of punishment. Interestingly, cooperators become abundant not because they avoid the cost of inflicting punishment and earn a larger average payoff per game but rather because they have more numerous opportunities to be referred as a role agent by defectors. Our results imply that the fluidity of social relationships has a profound effect on the adopted strategy in maintaining cooperation. p-1

Seasonal payoff variations and the evolution of cooperation in social dilemmas

“…During the last decade, methods of statistical physics and network science [26][27][28][29] have been successfully integrated into the mainstream research concerning the evolution of cooperation, revealing that the structure of the interaction network can be crucial [30][31][32][33][34][35][36][37][38][39][40][41][42][43][44]. It has also been thoroughly established that heterogeneity in general, for example in the form of heterogeneous networks, noisy payoff disturbances, or other individual properties like the teaching activity or the mobility to connect to additional other players, strongly promotes cooperation [45][46][47][48][49][50][51][52][53][54][55][56][57][58].…”

Reciprocity-based cooperative phalanx maintained by overconfident players

“…Here cooperator and defector strategies compete and to defect would always provide a higher individual income against a cooperator, but mutual cooperation would offer the optimal income for the whole community. In the last decades several cooperator supporting mechanisms were identified [6], * Electronic address: szolnoki.attila@energia.mta.hu † Electronic address: xiaojiechen@uestc.edu.cn including reward [7][8][9][10][11] or punishment [12][13][14][15][16][17], population heterogeneity [18][19][20], player's mobility [21,22], conformity [23,24] and tolerance [25,26], which could be helpful to avoid the tragedy of the common state when everyone chooses the tempting defection [27].…”

Competition and partnership between conformity and payoff-based imitations in social dilemmas

“…The proper coevolution revealed significantly different behaviors from those cases when we just apply the mentioned learning methods simultaneously in a static way via an external control parameter. In the latter cases players can only vary their strategies during the evolution [15,[24][25][26]. In other words, the significance of present study is to reveal the qualitatively different pattern formation mechanisms that we can only observe in a coevolutionary framework.…”