System structure can affect or decide the system function. Many pioneers have analyzed the impact of system’s macro-statistical characteristics, such as degree distribution and giant component, on system performance. But only few research works were conducted on the relation of mesoscopic structure and agent property with system task performance. In this paper, we designed a scenario that, in a multiagent system, agents will try their best to form a qualified team to fulfill more system tasks under the requirements from agent property, structure and task. The theoretical and simulation results show that the agent link network, agent properties and task requirement will co-affect the dynamic team formation and at last have serious effects on a system’s task completion ratio and performance. Some factors such as network density and task introduction period have positive influence. Task execution time and team size have negative influence. Some factors show a counter-intuitive influence. The clustering coefficient has not much influence as people expected and the task publicity time isn’t bigger the better. Notably, system performance is affected by the coupling effect, instead of the independent effects of all factors. The effect of system structure on system function conditionally relies on the support from agent ability and task requirement.

系统结构可以影响或决定系统功能。许多先驱者分析了系统的宏观统计特征，如度分布和巨分量对系统性能的影响。但对于细观结构和智能体属性与系统任务性能之间关系的研究却很少。本文设计了一个场景，在多智能体系统中，智能体在智能体属性、结构和任务的要求下，尽力组建一个合格的团队来完成更多的系统任务。理论和仿真结果表明，Agent链接网络、Agent属性和任务需求将共同影响动态团队形成，最终对系统的任务完成率和性能产生严重影响。网络密度、任务引入周期等因素具有正向影响。任务执行时间和团队规模有负面影响。有些因素显示出反直觉的影响。聚类系数并没有人们想象的那么大的影响，而且任务公示时间也不是越大越好。值得注意的是，系统性能受到耦合效应的影响，而不是所有因素的独立影响。系统结构对系统功能的影响有条件地依赖于Agent能力和任务需求的支持。