Public Goods Game Based On Dynamic Complex Networks

Darwin emphasized natural law that natural selection and survival of fittest,whether biological or human individuals would be selfish, would choose betrayalstrategy to maximize their own interests. There are some public resources or goodsinvolved several people, due to their competitive and scarcity characters and humanselfishness,“free rider” phenomenon will be appears, which will lead to a bad results.For examples, public traffic congestion, environmental pollution issues, biodiversitydestruction. However, in reality of nature and human society, the phenomenon ofcooperation widespread, if we can reduce the behavior of “free rider” and improvedegree of cooperation, thus the issues above will be resolved. So, studying theinteraction between selfish individuals is quite a interesting thing. The evolutionarygame theory that evolved from the classic and has a strict logical reasoning andmathematical framework provides a powerful tool to study the cooperation issues.The complex network of relatively recent concern provides a research tool forevolutionary game theory. In complex network node represents an individual involvedin the game, while an edge means game relationship between different individuals.Numerous studies show that coevolution of individual strategies of the game andnetwork structure can promote the emergence of cooperative behavior of thepopulation, so it has become a hot research.The main contents of this paper are, proposed public goods game based on dynamiccomplex networks through research on complex network of public goods game.Joined random disconnection and reconnection mechanism of edges on static complexnetwork, to explore which factors will affect the outcome of the game in the level ofcooperation. Firstly, simulation experiments found that dynamic network can promotecooperation than static network. The cooperation will increase with coefficient gains.When the probability of disconnection of type CD is greater than that of CC, cooperation will appear easier. Which suggest that we should try to keep touch withindividuals who willing to cooperate with us to maintain high level of cooperation.Then numerical derivation is used to confirm the results. The main methods used inthis paper are Monte Carlo simulation, Markov random process analysis andreplicator dynamics. The tools used mainly are Mat lab and Pajek. The innovation ofthis paper is considering in reality majority of network structure is not static,analyzing the public goods game of dynamic complex networks and using numericalanalysis the outcome.