Research On Co-evolution Dynamics Based On Individual Characteristics In Structured Population

Complex networks spread all over nature and human society,from Internet and mobile communication networks,power and transportation networks to economic and financial networks,social and biological networks,which all reflect the diversity of networks in the network era.Evolutionary dynamics in complex networks is the most valuable research direction in the field of network science.Evolutionary game theory,as a theoretical framework to understand and explain the cooperative behavior among rational individuals in the population,not only extracts the essential idea of the model from the complex phenomena and behaviors in the real world,but also serves as a methodology for explaining how individuals make decisions in social dilemmas.Based on this framework,the complex network is regarded as the structure of the system,and the game indicates the interaction between individuals.The various characteristics of individuals in complex environment are detailedly studied by Monte Carlo simulation,including the interaction between individuals,the influence of individual thinking and behavior on cooperative evolutionary dynamics.The main research contents and innovations are as follows:1.A prisoner's dilemma game model based on historical strategy and dynamic adjustment of interaction intensity is proposed.Under the framework of square lattice,the influence of historical strategy and dynamic adjustment of interaction intensity between individuals on cooperative evolution is studied.According to these two rules,the intensity of interaction between individuals is dynamically adjusted.When imitating strategies,the decisions between individuals are considered,and the opponent's strategies are imitated by Fermi-like updating rules.Numerical simulation shows that the dynamic adjustment of interaction intensity and consideration of historical strategy can effectively improve the cooperation among populations.Among them,the adaptive adjustment rules I and II of interaction intensity can promote the evolution of cooperation to a certain extent with the increase of interaction intensity range,but each has its advantages and disadvantages.Similarly,there is an optimal range of memory length,which makes cooperation reach a higher level.Finally,the current model is extended to evolutionary dynamics under mixed game,and its robustness is verified.2.A multi-game model based on the diversity of interaction intensity is proposed,in which two layers of networks are virtually connected through utility coupling,showing the characteristics of interdependence,and the utility of individuals mainly depends on the same layer,and is also influenced by individuals in the corresponding position individuals in another layer.In addition,two distinct interaction intensities between individuals are defined by the payoff differences,which reflects two completely different behaviors and represents the diversity of behaviors to a great extent.Numerical simulation shows that the diversity of interaction intensity,the benefit of the deceived and the utility coupling factor can promote the evolution of cooperation within population in their own way.The stronger the diversity of interaction intensity,the more obvious the level of cooperation within population will be enhanced,and the scope of complete cooperation will be greatly expanded.Finally,the complete b-K phase diagram further proves that the current model has greater advantages in modeling irrational behaviors in individual decision-making process.Therefore,under the complex social dilemma caused by multi-games,the diversity of interaction intensity is a powerful means to promote the development of cooperative behavior.