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In nature and human society, some agents want to obtain more payoffs by controlling own and opponents' strategy. The extortion strategy can unilaterally ensure that its own payoffs are not lower than its opponents', which has aroused widespread concern. In this article, based on spatial multigame, an evolutionary dynamics model with extortion strategy is proposed, which can significantly influence the evolution of different dilemma strategies in the system. Moreover, the limited resources as a co-evolutionary factor are also involved in this model. Throughout the entire evolutionary process, individuals in SDG and collaborators are more likely to obtain more resources and the number of resources owned by individuals in PDG is continuously decreasing. By using single square lattice network, we discuss in detail the evolutionary dynamics of the proposed model and study the impact of the sucker's payoff θ and extortion factor λ on different strategies of the system. Through a large number of experiments, it is found that the θ can significantly increase the number of cooperators. And there is an appropriate λ value, which can not increase the number of its own individuals, but also form an alliance with cooperators to jointly resist the intrusion of defectors. Besides, the relationship between θ , λ and network reciprocity is studied. We obtain that the θ and λ can significantly improve network reciprocity. Finally, based on different extortion factor λ , the proportion of different strategy in PDG and SDG is discussed to explain the robustness of the results. • Based on PDG and SDG, the model with extortion strategy is studied. • Limited resources are introduced into the system as a co-evolutionary factor influencing the agents. • The relationship between the sucker's payoff, extortion factor, and network reciprocity is studied. [ABSTRACT FROM AUTHOR]

In real life, some individuals generally have more influence than ordinary people. Their behaviors are easily learned by other individuals. In this article, we propose influence-based preferential selection multi-games model on interdependent networks, where influence of players as a factor to be considered is involved in multiple game models and coevolved with cooperation. By using of coupled lattices, the effect of the cooperative behaviors of the system is comprehensively studies. Besides, in real life, resources are always related to the outcome of game. The results in game generally determine the allocation of limited resources, which in turn affects the choice of strategy. Hence, limited resources as a co-evolutionary factor are also introduced into the game model, which mutual interacts with individual's strategy and influence. Based on multi-game model, the evolutionary dynamics of the model in detail is discussed. We find that the preferential selection mechanism based on influence can effectively improve the cooperative behaviors of the system, where the influence growth factor increases and the cooperation evolution also monotonously increases. Furthermore, the interdependent strength, sucker's payoff and the distribution of limited resources would have different effects on the dynamics of the system. [ABSTRACT FROM AUTHOR]