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中文摘要：
基于进化博弈理论,实现了用于服务商动态联盟协同管理工作的多智能体模拟系统,并进行模拟数据分析。扩展传统对称静态博弈为含惩罚参数和协同效率参数的离散进化博弈情形,设计一种含历史信息和近邻特征的群体进化学习规则;在Repast基础上,用java编程实现了多加盟企业进化博弈Agent模拟系统并进行分析。结果表明：agent规模数对平均收益影响小,具有不同决策特征的agent的比例分布能改变企业的平均收益,不同协同率、沟通方式和惩罚参数对期望收益有影响。为电子商务和移动商务环境下的动态联盟管理决策提供参考。
英文摘要：
Based on the evolution game theory,the multi-agent systems is implemented,the system can be used to supporting collaborative management for dynamic coalition.Extended the traditional symmetric game to the discrete evolution game,which includes collaborative coefficient and punishment parameter,then designed evolution learning rules including historical information and neighbor characters,and applied java to programming the group evolution game agent simulation system based on Repast.Simulation analytical and numerical results lend insight into how impacts on the profit expectations in the several different size of individuals,different proportion of individual distribution,different communication mode and punishment parameters,which contribute some decision support for dynamic alliance under the environment of e-commerce or mobile commerce.
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