CAJ | 학술논문

将“演化的争当少数者博弈”模型(EMG)建立在41×41的二维正方形网格上，格点代表经纪人，连线代表该两相邻经纪人存在联系，每个经纪人被随机分配一个介于0与1之间的基因策略p值。数值模拟结果表明：模型的奖惩比等于或大于1时，随着演化过程的进行，系统经纪人倾向于模仿具有极端基因策略值(接近0或1)经纪人的策略，说明极端的决定策略比犹豫策略(接近0.5)的表现要好，能使经纪人获得更大收益；当经纪人策略自组织分离现象出现后，人群-反人群效应更加明显，系统一方人数的变化偏差显著降低，系统资源得到更加有效的利用.而当模型的奖惩比小于1时，即处于困难时期时，中间犹豫策略的表现则比极端策略要好.
장“연화적쟁당소수자박혁”모형(EMG)건립재41×41적이유정방형망격상，격점대표경기인，련선대표해량상린경기인존재련계，매개경기인피수궤분배일개개우0여1지간적기인책략p치。수치모의결과표명：모형적장징비등우혹대우1시，수착연화과정적진행，계통경기인경향우모방구유겁단기인책략치(접근0혹1)경기인적책략，설명겁단적결정책략비유예책략(접근0.5)적표현요호，능사경기인획득경대수익；당경기인책략자조직분리현상출현후，인군-반인군효응경가명현，계통일방인수적변화편차현저강저，계통자원득도경가유효적이용.이당모형적장징비소우1시，즉처우곤난시기시，중간유예책략적표현칙비겁단책략요호.
With EMG model on 41×41 two-dimensional lattice, lattice point represents agent, ligature represents communication of two neighbouring agents, and each agent is assigned a gene strategy p value between 0 and 1 randomly. Numerical simulation shows that when prize-fine ratio of model is equal to or larger than 1, with proceeding of evolution, agents in system tend to imitate the strategy of agents who have extreme gene strategy(near 0 or 1), which shows extreme strategy performs better than hesitate strategy(near 0.5), and may brings more benefit to agents; when self-segregation phenomenon of agent strategy appears, crowd-anticrowd effect is more evident, the variance of the number of agents in one side reduces significantly, the system resource is utilized more efficiently. When the prize-fine ratio is less than 1, namely in difficult period, middle hesitate strategy performs better than the extreme strategy.