中文摘要：

基于进化博弈视角，对人群工作互动行为进行多智能体模拟研究．建立了收益和惩罚共享的群体工作收益博弈模型，考虑工作个体的个性决策特征，设计基于历史信息和个体决策特性的混合学习规则，并用多智能体方法对群体工作场景进行描述．在Repast类库基础上，用Ja—va实现该多智能体模拟系统．模拟结果表明：1）群体规模对宏观工作趋势影响小，但对合作频率影响大；2）工作总收益b越大，越有利于工作人群的工作状态稳定．当工作付出c与惩罚d相当时，群体行为呈针锋相对态，当工作付出大于惩罚时，背叛占优，反之，则合作占优；3）工作难度对群体行为有影响．高难度下，群体行为不稳定，获利低，风险大，而低难度下，群体行为稳定，获利高，风险小；4）由具有不同比例决策特性个体组成的群体工作收益和状态各异，保守型和中立个体较多时，合作比例大，而获利也多．该研究可为电子／移动商务环境下的工作行为管理问题提供决策支持．

英文摘要：

Agent-based simulation for interaction behavior between group and work was explored from an evolutionary game-theoretical perspective. This paper develops a payoff-shared and punishment-shared game model, design evolution learning rules considering of historical information and decision characteristic of neighbors, and uses multi-agent approach to represent group work. Based on class lib of Repast, we use Java 2 to program the multi-agent simulation system. Simulation results indicate that （ 1 ） the size of work group has a minor effect on cooperation trend and major effect on cooperation frequency of group, （2） total work payoff b has a positive effect on the stability of work state of group. Group behavior is in a state of Tit-for-Tat when work cost c is equivalent to work punishment d, more players want to cooperate when c 〉 d, and vice versa, the more players wants to defect when c 〈 d, （3） group behavior in doing highly difficult work is unstable, players can get lower profit from more highly difficult work with larger risk, or vice versa; and （4） groups made up of individuals with different decision-making characteristics have different effects on the work state of group. The number of conservative and neutral individuals has a positive effect on cooperation and profit. This study contributes some decision support to behavior management under E-commerce or Mobile commerce environment.