A Study Of Several Evolutionary Game Strategies Based On Complex Networks

In recent years, the cooperative evolution dynamics research on complex networks has become a popular topic in the field of interdiscipline. The combination of complex networks and evolutionary game theory provides a convenient theoretical framework to study the emergence and maintenance of cooperation behavior between selfish individuals. We mainly investigate the cooperative evolutionary dynamics on complex networks and firstly introduce the relevant theoretical knowledge of the complex networks and the evolutionary game theory. Then, we establish several effective rules to promote cooperative behavior based on different complex networks. The main innovation points are as follows:1. Based on the classical ultimatum game, we develop a multi-person ultimatum game on complex networks. Then we investigate a mixed model on the basis of the classical ultimatum game and the multi-person ultimatum game. The simulation shows that our multi-person model which is similar to the way of election can promote the generation of fairness; we consider mixed ultimatum game on twointerdependent networks through internal connection, in which those generous individuals can make connection with the corresponding individual on the other network, and the two individuals could play the classical ultimatum game.On their own network individuals play the multi-person ultimatum game. The final profit of the individual which has connection with the corresponding individual on the other networkis not only affected by its own group earnings but also affected by the additional connection benefits. Such a mechanism could effectively promote the fairness. In this paper, we develop such a mechanism in order to provide a theoretical basis to further explain the widespread social fairness.2. We explore evolutionary dynamic probability connection rule on two interdependent networks. In this rule, each individual are firstly assigned a certain probability connection value. Then, each individual will adjust their probability connection value according to the corresponding individual’s strategy, the final connection probability is the product of both two. Ultimately each individual’s final profit depends not only on the individual’s payoff getting from its own network, but also be affected by the influence of the corresponding individual’s payoff value. There exists a certain couplingbetween two networks. This rule forms a reward system for those individuals who choose the cooperative behavior, and make them have the opportunity to obtain a relatively large profit. The simulation shows that the connectio n probability rule is substantially beneficial for the emergence and persistence of cooperation.