分布式自利agent任务分配算法

Task Allocation for Distributed Self-Interested Agents

在有自利agent参与的任务分配情形中,由于agent的自利性,导致各agent不能有效合作,影响agent的个体收益和系统总收益.解决该问题的一个途径是对agent所得的收益进行合理分配.文中基于分布式自利agent联盟技能博弈模型,提出自利agent的任务分配算法.模型中提供技能的服务agent和管理任务的agent都是自利的,分别处于不同的地理位置,具有不同的视野范围.算法为任务agent设计效益分配策略,合理分配自己的收益给所需的技能,任务分配结果在保证个体自利性的前提下获得较高的系统收益.仿真结果验证文中算法的有效性,并考察自利agent的视野范围对自利agent的个体收益和系统总收益的影响.

In the task allocation with self-interested agents,the agents cannot cooperate effectively due to their selfishness and thus their individual revenues and system performance are decreased. To make a reasonable distribution of the utilities,a self-interested agent task allocation algorithm based on the task allocation model of a distributed self-interested agent coalitional skill game is proposed. The service agents and the task agents are self-interested. They are located in different geographic locations with different scopes of vision. The utility distribution strategies are designed for task agents to make them reasonably distribute their utilities to each required skill. The task allocation results guarantee a higher system revenue even if the agents are all self-interested. The final simulation results verify the effectiveness of the proposed algorithm and examine the impacts of the scope of vision of the selfinterested agents on their individual revenues and system performance.