计算机科学 ›› 2009, Vol. 36 ›› Issue (9): 186-192.

• 人工智能 • 上一篇    下一篇

基于多值表示的并行规划方法

史晶晶,刘大有,蔡敦波,吕帅,江鸿   

  1. (吉林大学计算机科学与技术学院 长春 130012);(吉林大学符号计算与知识工程教育部重点实验室 长春 130012)
  • 出版日期:2018-11-16 发布日期:2018-11-16
  • 基金资助:
    本文受国家自然科学基金重大项目(60496321),国家自然科学基金项目(60573073,60503016,60603030,60773099,60703022,60873149),国家863高技术研究发展计划项目(2006AA10Z245,2006AA10A309),吉林省科技发展计划重点项目(20060213),欧盟项目TH/Asia Link/010(111l084)资助。

Parallel Planning Based on Representation with Multi-valued State Variables

SHI Jing-jing,LIU Da-you,CAI Dun-bo,LU Shuai,JIANG Hong   

  • Online:2018-11-16 Published:2018-11-16

摘要: Fast Downward规划系统是第四届国际规划竞赛的冠军。以高效的串行规划系统Fast Downward为基础,设计并实现了并行规划系统Parallel Downward。首先提出4个并行规划的相关定义;之后提出多值规划任务下动作互斥的定义、充要条件,并实现了动作互斥判断算法;在此基础上设计了候选并行动作集的生成算法;然后为提高系统求解质量重新设计了新的搜索控制策略;最后,给出剪枝策略来抑制并行规划状态空间的指数级膨胀。通过对国际规划竞赛测试问题的实验,Parallel Downward表现出良好的规

关键词: 并行规划,多值规划任务,状态空间启发式搜索,因果图启发式

Abstract: Fast Downward had won the classical track of the 4th International Planning Competition at ICAPS 2004, our work extended the Fast Downward planning system to a parallel setting, and implemented a parallel planning system called Parallel Downward. Several techniques were proposed in this paper. Firstly, four definitions related to parallel plan were given. Secondly, we proposed a method to decide mutual exclusive actions in multi-valued planning tasks, ineluding definitions, the necessary and sufficient condition and the deciding algorithm. Thirdly, we designed an efficient generation of successor states with low cost of generating all the legal sets of actions. Finally,we proposed an effective search control policy of parallel planning to enhance the quality of this valid plan. In addition, we proposed the pruning policy to restrain state space of parallel planning exploding exponentially. We tested Parallel Downward on planning benchmarks used in the International Planning Competitions. The experimental results show that Parallel Downward is excellent in both planning efficiency and planning quality. Parallel Downward is superior in scalability compared with Sapa parallel planning system.

Key words: Parallel planning, Multi-valued planning task, Planning as heuristic search in state space, Causal graph heuristic

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