计算机科学 ›› 2012, Vol. 39 ›› Issue (6): 226-230.

• 人工智能 • 上一篇    下一篇

基于动态约束满足框架的强表达时态规划算法

刘越畅   

  1. (嘉应学院计算机学院 梅州514015)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Expressive Temporal Planning Algorithm under Dynamic Constraint Satisfaction Framework

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

摘要: 智能规划已经成为人工智能领域最热门的研究主题之一。近年来,智能规划在现实领域的应用越来越广泛,这对规划器的处理能力和效率提出了很大的挑战。以一类强表达时态规划—基于约束区间规划为研究对象,基于动态约束满足框架设计和实现了一个基于约束区间的规划算法LP-TPOP;对算法的可靠性和完备性进行了证明;最后以一个规划实例演示了算法的运行过程。

关键词: 智能规划,强表达时态规划,动态约束满足问题,算法

Abstract: AI planning has been the key research topic in artificial intelligence(AI) community. In recent years, AI planning technology has been applied to solve many real-world problems, which gives a challenge for AI planner both in handung power and efficiency. This paper studied a kind of expressive temporal planning paradigm-constraint based interval(CBI) planning. Based on the dynamic constraint satisfaction problem framework, the author designed a new CBI algorithm named LP-TPOP. hhe paper gave the proof of soundness and completeness for LP-TPOP, and algorithm demonstration for a CBI planning example.

Key words: AI planning, Expressive temporal planning, Dynamic constraint satisfaction problem, Algorithm

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