Reward And Punishment Mechanism Of Evolutionary Game Based On Attitude And Information

With the rapid development of Internet technology,information dissemination methods and channels become more and more diversified,and the frequency of information interaction between people is also greatly improved.Due to the differences between individuals,different people will have different views and reactions to the same thing due to the differences in thinking concepts and information acquisition.When individuals interact with each other,there is a great probability that they will be affected by each other and lead to the change of behavior and attitude.The differences in behavior strategies will lead to different benefits for individuals in the process of interaction,and each individual will get different benefits from others.In the process of individual interaction,they tend to choose the strategy of maximizing the interests,but as a part of the social group,they also choose to sacrifice part of the interests for the long-term development of the group to maintain system stability and mutual interests.Therefore,what kind of behavior is more advantageous,and when individuals choose to cooperate have gradually been widely concerned;how to influence individuals through reasonable means,so that they can promote the development of the system towards long-term profits on the basis of ensuring their own profits,has also been a lot of research.Through the research and experiments of various evolutionary dynamic models on social networks,we can better and more accurately describe the social phenomena among and within various groups in real life.This paper constructs a dynamic evolutionary game model of reward and punishment mechanism based on the amount of information and the attitude of group and individual by comprehensively considering the multiple factors of social groups in the external environment and internal evolution.The main work of this paper is as follows:Firstly,on the basis of the existing research,based on the repeated prisoner's dilemma game model,the network with variable link weight is improved to make it more in line with the characteristics of social networks in real life;then,the external event information is introduced as the external factor that affects the behavior strategy among individuals in the network,and the subjective initiative of individuals is comprehensively considered,and the reputation value and external inflow within the network are used The amount of information is used as the main basis and presentation form of reward and punishment mechanism to study the influence of internal and external factors on the evolution of individual cooperative behavior.The research proves that,combined with the improved model,even if there are free riding individuals,in the long run,the inflow of external event information stabilizes the status of strategic individuals with high reputation,and promotes the emergence of group cooperative behavior.Finally,through mathematical analysis,the pressure matrix of individuals in different states is constructed,and the boundary conditions of network stability are analyzed Based on the above theoretical analysis,a reward and punishment mechanism based on group and individual attitude is constructed and added to the model.It is found that the reward and punishment mechanism can promote the cooperative behavior in the network,especially in the early stage of evolution,by taking advantage of the characteristics of individuals' desire to reduce pressure and pursue stability.Combining the two kinds of reward and punishment mechanism,it can be concluded that the combination of internal and external factors can promote the network to reach a stable state faster,and the emergence of cooperative behavior has increased significantly.On the other hand,compared with the existing research,this model and reward and punishment mechanism are more practical and more suitable for the actual situation.