摘要
多智能体任务规划中的任务分解、任务协调是相互关联和紧密结合的过程。与或树是人工智能中用于表示问题规约以及求解过程的一种方法,它能把复杂的多阶问题分解成多个易于求解的子问题。针对任务的复杂性和时序约束问题,提出一种结合带权与或树和AOE-网的任务规划方法。根据任务的时序约束,对复杂任务进行逐层分解或变换,建立带权与或树结构;将带权与或树转换为AOE-网,进行基于最早发生时间的任务计划一致协调。仿真结果验证了任务规划方法在多智能体系统中的可行性和有效性。
Task decomposition and task coordination are interrelated and closely integrated process in multi-agent systems task planning.And/or tree is used to indicate the problem statute and solving process in artificial intelligence,with that a complex multi-stage problem is decomposed into several sub-problems which are easily solved.With regards to the complexity of the tasks and timing constraints,a task planning combined weighted and/or tree and AOE-network is presented.According to timing constraints between tasks,complex tasks are decomposed or transformed layer by layer,a structure of weighted and/or tree is built.Then the weighted and/or tree is converted to an AOE-network,concerted planning coordination is executed based on the earliest time of occurrence.Simulation results demonstrate the feasibility and effectiveness of task planning method.
出处
《计算机工程与应用》
CSCD
北大核心
2011年第19期49-53,共5页
Computer Engineering and Applications
基金
国家自然科学基金No.60874042~~
关键词
带权与或树
AOE-网
多智能体
任务规划
任务分解
任务协调
weighted and/or tree
AOE-network
multi-agent systems
task planning
task decomposition
task coordination
