期刊文献+

基于动态约束满足框架的强表达时态规划算法 被引量:3

Expressive Temporal Planning Algorithm under Dynamic Constraint Satisfaction Framework
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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。 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 handling 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.The paper gave the proof of soundness and completeness for LP-TPOP,and algorithm demonstration for a CBI planning example.
作者 刘越畅
出处 《计算机科学》 CSCD 北大核心 2012年第6期226-230,共5页 Computer Science
基金 梅州市科学技术局 梅州市科技计划项目(梅市科(2011)3号) 嘉应学院联合自然科学研究项目(2010KJA06) 嘉应学院科研启动经费项目资助
关键词 智能规划 强表达时态规划 动态约束满足问题 算法 AI planning Expressive temporal planning Dynamic constraint satisfaction problem Algorithm
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参考文献20

  • 1Green C. Application of theorem proving to probl-a solving [-C/// Preceedings of UCAI. Washington DC, USA, 1969 .. 741-747.
  • 2Traverso P,Ghallab M, Nau D. Automated planning;theory and practice EM3. San Francisco; Morgan Kaufmann Publishers, 2004.
  • 3Smith D, Weld D S. Temporal planning with mutual exclusion rea- soning [- C3 /,/ Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence. Stockholm, Sweden, July- August, 1999 : 326-337.
  • 4Fox M, Long D. PDDL2.1 : An extension to PDDL for expres- sing temporal planning domains ['J-]. In Journal of artificial intel- ligence research, 2003,20 : 61-124.
  • 5Fikes R E, Nilsson N J. STRIPS: A new approach to the applica- tion of theorem proving to problem solving I-J-]. Artificial Intelli- gence, 1971,2 (3/4) : 189-208.
  • 6McDermott D. PDDL: the Planning Domain Definition Language I-R. CVC TR-98-003/DCS TR-1165 ,Yale Center for Computa-tional Vision and Control, 1998.
  • 7Bacchus F. The power of modeling-a response to PDDL2. 1 EJ]. J. Artificial Intelligence. Res. (JAIR), 2003,20 : 125-132.
  • 8Cushing W, Mausam, Kambhampati S, et al. When is Temporal Planning Really Temporal? VC] ff Proceedings of IJCAI 2007. Hyderabad, India,January 2007 : 1852-1859.
  • 9Smith D E. The case for durative actions: A Commentary on PD- DL2. l[-J]. Journal of Artificial Intelligence Research, 2003,20 : 149-154.
  • 10Smith D E, Frank J, Jonsson A, et al. Bridging the Gap between Planning and Scheduling EJ. Knowledge Engineering Review, 2000,15(1) ;47-83.

二级参考文献20

  • 1Stergiou K, Koubarakis M. Backtracking algorithms for disjunctions of temporal constraints [C] //Proc of the 15th National Conf on Artificial Intelligence (AAAI-98). Menlo Park: AAAI Press, 1998:248-253
  • 2Federico B. Reasoning on interval and point-based disjunctive metric constraints in temporal contexts [J]. Journal of Artificial Intelligence Research, 2000, 12:35-86
  • 3Laborie P, Ghallab M. IxTeT: An integrated approach for plan generation and scheduling [C] //Proc of the 4th IEEE- INRIA Syrnp on Emerging Technologies and Factory Automation (ETFA'95). Los Alamitos: IEEE Computer Society, 1995:485-495
  • 4Weld D. An introduction to least commitment planning [J]. AI Magazine, 1994, 15(4): 27-61
  • 5Dechter R, Meiri I, Pearl J. Temporal constraint networks [J]. Artificial Intelligence, 1989, 49(1/3) : 61-95
  • 6Eddie S, Rina D. Processing disjunctions in temporal constraint networks [J]. Artificial Intelligence, 1997, 93 (1/2) : 29-61
  • 7Alessandro A, Claudio C, Enrico G. SAT based procedures for temporal reasoning [C]//Proc of the 5th European Conf on Planning. Berlin:Springer, 1999
  • 8Oddi A, Cesta A. Incremental forward checking for the disjunctive temporal problem[C]//Proc of ECAI 2000. Amsterdam: IOS Press, 2000: 108-112
  • 9Tsamardinos I, Pollack M E. Efficient solution techniques for disjunctive temporal reasoning problems [J]. Artificial Intelligence, 2003, 151(1/2) : 43-89
  • 10Alessandro A, Castellini C, Giunchiglia E, et al. Tsat++ : An open platform for satisfiability modulo theories [G] //Proc of PDPAR 2004, ENTCS, 125 (3). Amsterdam: Elsevier Science Publishers, 2004 : 25-36

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