Research On Naming Game Between Communities Based On Complex Networks

Many systems in nature and human society have a high degree of complexity.If they are abstracted into a complex network of nodes and connection relationships in accordance with certain rules,it will help people to explore the laws of the real world.The development of the Internet has provided technical support for complex networks and made complex network research an object of concern.Scientists explore the inherent laws in the real world to build complex network models that meet the characteristics of real networks,and discover the characteristics of real networks from the process of analyzing complex networks.The study of complex networks not only has important significance for the development of complexity science itself,but also provides a prerequisite and guarantee for the exploration of dynamics.As one of the important components of social dynamics,the naming game is a game model that studies the formation and evolution of language on a complex network.It simulates the self-organized interaction of individuals with zero supervision and organization on a complex network to a point of view.In recent years,a large number of achievements in the study of naming games on complex networks have provided important references for the evolution of reduced languages.On the premise of consulting a large number of domestic and foreign literature on naming games on complex networks,this article summarizes the classic models and current research status of complex networks and naming games.From previous research,it has been found that the topological structure and properties of the complex networks used in naming games will have a certain impact on the evolution of convergent vocabulary.To explore the rules of vocabulary convergence on community networks,the following works were done:1.By referring to the construction process of the BA network,an inter-community borderline network model construction method is proposed.This method refers to the famous Google page ranking algorithm PageRank algorithm to calculate the importance of nodes in the network,and according to the calculated node importance metric Value and degree of the node in the network to select the node that establishes the connection.At thesame time,the degree of coupling between communities is introduced as a measure of the intensity of communityization,and the relationship between related parameters and the degree of coupling between communities is analyzed.2.Apply the network edge model to multi-community networks and choose the smallest naming game to evolve on the constructed network model.It is found that the degree of coupling between communities will affect the number of final vocabulary convergence.The more obvious the community of the network is,the easier it is for the vocabulary to form local convergence.When the community-to-community connection reaches a certain level,the vocabulary evolved on the Internet can eventually be unified.3.Select different naming game models to evolve on the network.By analyzing the changes in the total vocabulary,different vocabularies,and average protocol success rates,it is found that as the network community decreases,the convergence of the vocabulary of different game models tends to be unified,and the limited memory naming game model under the same network is more conducive to vocabulary convergence.4.Comparing the convergence speed of vocabulary under different community coupling degrees,it can be found that the stronger the community,the faster the local convergence of the network.At the same time,different naming game models,choice of strategies,and the average degree of nodes in the network will all affect the convergence speed of the vocabulary.