基于multi-agent的多任务分配问题研究  

Multi-task allocation problem research based on multi-agent

作　　者：刘科[1] 郭小和[1] 周继强 卢永乐[1] 

机构地区：[1]南昌航空大学飞行器工程学院,南昌330063 [2]中航工业洪都飞机设计研究所,南昌330024

出　　处：《计算机应用研究》2014年第7期1980-1983,1988,共5页Application Research of Computers

基　　金：航空科学基金资助项目(2010ZC66009);中航工业创业基金资助项目(2012Q32022)

摘　　要：传统的多agent多任务分配往往采用集中式的分配方法。由于集中式分配方法存在计算量大且易造成通信拥塞的不足,近年来又产生了各种分布式分配算法,但分布式算法容易陷入局部最优,影响分配效果。针对动态环境中任务复杂多样且agent能力差异,提出一种agent通信与结构框架,通过三个层次将集中式与分布式相结合,反馈地引入有利于分配过程的优化。根据任务的时间窗口和agent的代价设计合理的任务回报函数,提出一种分布式任务分配算法,对多任务进行合理分配,同时保证算法的鲁棒性。仿真结果表明,与单纯的集中式和分布式任务分配方法相比,混合系统能够完成全部的任务,且获得与集中式相当的任务收益,对框架下的各个agent的能力进行了充分利用,验证了通信与结构框架以及所提任务分配算法在动态环境多agent多任务分配过程中的有效性和合理性。Traditional multi-agent multi-task allocation often used centralized allocation method,however,it had many drawbacks,such as require a large amount of computational and cause network congestion easily,so different distributed allocation algorithms were arise in recently. While these algorithms were easy to fall into local optimal and affect distribution effects,this paper proposed an agent communication and structure framework according to diverse complex tasks in a dynamic environment and agent＇s capacity variance,and through three levels to combine centralized with distributed,the introduction of feedback was in favor of optimal allocation process. It put forward an distributed task allocation algorithm in order to obtain reasonable scheme based on task time windows and agent fuel cost,while ensuring the robustness of the algorithm. Simulation results show that hybrid system could accomplish all the tasks and acquire fairly task revenues as the centralized method,and make full use of the agent＇s ability. Verifying communication and structure framework and task allocation algorithm for multi-agent multi-task proposed algorithms is effectiveness and rationality in dynamic environment.

关 键 词：层次分配 分布式 集中式 混合系统 任务分配 时间窗口 协同控制 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术] V219[自动化与计算机技术—计算机科学与技术]