Evolutionary Public Goods Game And Smart-strategy In Complex Game

Game theory provides a strong theoretical framework to explain the interactions amongselfish individuals. Since the "Theory of Games and Economic Behavior" by mathematicianVon Neumann and economist Morgenstern published, People began to follow the GameTheory to analyze the problems of economic competition, military conflict and evolution ofspecies, especially biologists Smith introduced Game Theory into the field of biologicalevolution and tried to understand the evolution population using the game point of view.Individuals as nodes and links between individuals as the edges, then the organizational formof the population can be described by the network. There is a growing focus on the interactionbetween the different network structures and selfish individual behavior. Studies have shownthat if the selfishness of individuals to choose their behavior the system will be in theinefficient state. Therefore, we need to introduce appropriate measures to regulate thebehavior of selfish individuals to optimize system performance.This article will focus on the connotation of the individual's strategies. Based on theessential characteristics of the agent, we expand the meaning and structure of strategy. Weintroduce space-time dimensions for the earlier, less humble game model, making the modelmore realistic. Agent strategy has been extended in time and space to reflect the elements ofthe basic smart. That provides a greater vision for our research, the result is more in line withcommon sense, and can give a better explanation for various phenomena in nature. We expectto give more effective guidance for the variety of life in human society.The main contribution of this article as well as research results are as follows:1. Population structure takes a deep impact on evolutionary dynamics. The evolutionaryprocess of a well-mixed population can be very different from that of a structured population.We refer to an evolution model of set structured populations. In this model, both individuals strategies and population structure are subject to evolutionary updating. We specially focus onthe evolution of cooperative behavior and study the dynamics of evolutionary public goodsgame in set structured populations. Some key parameters affecting the population s evolutionand various dynamic nature showed during the process of evolution are studied by approachescombining theoretical analysis and computer simulations. We found that the co-evolution ofboth strategies and sets structure can promote cooperation in public goods game. The model advised by us also can be extended and provide new research ideas for more otherevolutionary multiplayer game.2. Memory is one of the most basic abilities that agents generally have. However, thisfact is usually ignored by most of the researches on evolutionary game theory. In traditionalevolutionary game theory, each individual takes either a pure strategy or a mixed strategywhich are both a priori and fixed. But in reality individuals always make decisions dependingon their experiences and specific situations. Thus we introduce a new strategy calledsmart-strategy and then study the evolutionary dynamic of a well-mixed population whereagent is modeled to have a memory. The smart-strategy allows individual be able to decideaccording to historical actions information in memory. Specially, we used some basicthoughts of subliminal channel for reference and then put forward some innovativeviewpoints on how to design the smart-strategy. We used an approach combining theoreticalanalysis and computer simulations to investigate the various nature of smart-strategy and thedynamic of system's evolution. It is found that when meeting certain requirements forparameters the smart-strategy will make the traditional evolutionarily stable strategy (ESS)lose the original standard of evolutionary stability.3. Evolutionary Game Theory is important tool for studying population evolutionary incomplex system. We brought intelligent strategy model in Game Theory and introduce the"Complex Game". An intelligent fitness-reaction strategy model which based onfitness-reaction decision-making model and two-branch logical algorithm was defined. Wefound that the new model could get a steady state with larger average revenue than traditionalmodel in "Complex Game".