Research On Group Game Behavior On Multi-layer Complex Network

Human beings are the most typical gregarious creatures.As gregarious creatures,human beings walk in various social relationships.The concept of complex network can be used to abstract social relationships and form multi-layer complex networks through superposition,such as multi-layer social networks and multi-layer transportation networks.Existing studies have pointed out that complex networks simplify the characterization of individual game relationships,while game theory endows individuals with rational decision-making behaviors in networks.The application field of game theory is very wide,from chess leisure and entertainment activities to national political affairs negotiations,all of which embody game theory ideas.With the in-depth study of complex networks and game theory,people began to integrate game theory ideas into complex networks to study the factors that affect individual game behavior.Most of the existing studies are single-layer complex networks,which cannot fully simulate the complexity of real networks.The game models on complex networks are basically two-player games,which cannot describe the real scene of multi-person group games in reality.Based on the above limitations,this paper combines multi-layer network and group game,and introduces reputation and heterogeneous investment factors into the traditional public goods game model,and studies the public goods game based on reputation-heterogeneous investment on multi-layer complex network.The specific work is as follows:(1)This paper builds a static single-layer and double-layer network.The network model selects the most realistic NW(Newman and Watts)small-world network and BA(Albert-László Barabási and Réka Albert)scale-free network to simulate the real-world network environment.By comparing the differences in the evolutionary behaviors of group games on different types of networks,we explore the factors that affect individual game behaviors.Then,the reason for this phenomenon is further explored by changing the key parameters in the multilayer network.The experimental analysis shows that:when the game is played in a two-layer NW network,the density of partners is not as good as that of a single-layer network;the lower the learning probability of different layers in a two-layer network,the better the cooperation effect.And when the sum of the gain factors of the two-layer network is constant,the cooperation level of the network is within a fixed range.However,in the BA network,the influence of the learning probability of different layers on the cooperation effect needs to be discussed separately according to the value of the gain factor.When analyzing the heterogeneous investment factors,it is found that when the gain factor r value is fixed in the two-layer NW network,the larger the heterogeneous investment factor ?,the greater the density of partners,and the faster it tends to balance.Comparing the two-layer networks with different learning probabilities between layers,it is found that both can promote cooperation to a certain extent.(2)This paper designs a multi-layer network with dynamic topology capability,which is used to imitate the dynamic social situation of individuals,realizes the coevolutionary behavior of network topology and strategy selection,and proves that the adaptive adjustment of strategy and structure can effectively promote cooperation and promote cooperation.keep it steady.(1)In the dynamic network experiment,the NW network as the basic network model is compared with the game in the static multi-layer network,and the experimental results are found to be consistent.When the gain factor takes a small value,the learning probability of different layers can promote the increase of the collaborator density.In contrast,the dynamic two-layer network is more capable of producing cooperative behavior than the static two-layer network.But when the network has dynamic topology capability,the single-layer dynamic network is more stable than the two-layer dynamic network.(2)In a dynamic two-layer network,no matter what the value of the heterogeneous investment factor is,the cooperator density increases with the increase of the gain factor.Under the same gain factor,the greater the heterogeneous investment factor,the greater the collaborator density.Because the heterogeneity factor introduces the effect of reputation,the investment amount can be adjusted according to the game environment,and to a certain extent,it inhibits the betrayer with high reputation value from free-riding to obtain high returns.In conclusion,by introducing reputation value and heterogeneous investment factors into the game model,this paper better simulates the investment scenarios in real life.And this experiment is carried out on a multi-layer network,which provides a theoretical basis for people to invest in multiple fields in reality,and reduces the damage caused by unfavorable investment to a certain extent.