关键词: public goods game, evaluation effect, fitness, network reciprocity

Abstract: Payoff-driven strategy updating rule has always been adopted as a classic mechanism, but up to now, there have been a great many of researches on considering other forms of strategy updating rules, among which pursuing high fitness is one of the most direct and conventional motivations in the decision-making using game theory. But there are few or no researches on fitness from the perspective of others' evaluation. In view of this, we propose a new model in which the evaluation effect with fitness-driven strategy updating rule is taken into consideration, and introduce an evaluation coefficient to present the degree of others' evaluation on individual's behavior. The cooperative individuals can get positive evaluation, otherwise defective individuals get negative evaluation, and the degree of evaluation is related to the number of neighbors who have the same strategy of individual. Through numerical simulation, we find that the evaluation effect of others can enhance the network reciprocity, thus promoting the cooperation. For a strong dilemma, the higher evaluation coefficient can greatly weaken the cooperation dilemma; for a weak one, the higher evaluation coefficient can make cooperator clusters spread faster, however, there is no significant difference in the level of cooperation in the final stable state among different evaluation coefficients. The cooperation becomes more flourish as the number of fitness-driven individuals increases, when all individuals adopt fitness-driven strategy updating rule, the cooperators can quickly occupy the whole population. Besides, we demonstrate the robustness of the results on the WS small-world network, ER random network, and BA scale-free network.

Key words: public goods game, evaluation effect, fitness, network reciprocity