Abstract
In this paper, we mainly probe into the evolution of cooperation in the spatial public goods game on interdependent lattices by introducing the reputation inferring mechanism into the strategy selection. During the strategy update, the individual reputation is commonly determined by two corresponding partners on interdependent lattices, where the imitated neighbors are chosen in accordance with the average, maximum and minimum of reputation values between two partners within the neighborhood of a focal player. A large plethora of simulations indicate that three reputation computing rules all lead to the promotion of cooperation when compared to the traditional public goods game model. Among them, the promotion of cooperation under the average and minimum schemes are relatively better than that produced by the maximum rule. The detailed cluster formation and reputation distribution are provided to illustrate the slight difference between the outcomes under these three decision making criterions, in which the choice of learning objects is governed by their reputations. Thus, we can conclude that current results are further conducive to understanding the universal and persuasive cooperation within many natural, biological, social and even man-made systems.
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