期刊文献+

并行概率规划综述 被引量:3

Survey on parallel and probabilistic planning
下载PDF
导出
摘要 自动规划针对特定领域的特定问题,生成一个由可应用动作构成的规划。经典规划中的动作效果是确定的,且在每个时间步内只能执行一个动作。但在实际问题中,动作的效果往往是不确定性的,且动作的执行具有并发性。因此,并行概率规划(parallel and probabilistic planning,PPP)被提出,并且它的应用前景正在引起规划研究学术圈的关注。有鉴于此,对其进行综述,具体内容包括定义PPP领域、问题和规划解,介绍其描述语言、基准领域及规划器,并对其中两个有代表性的规划器进行实际测试。实验表明在求解效率方面测试结果与比赛结果基本一致,但部分规划器的求解规模与竞赛不完全一致。这可能是比赛中的某些未开源代码或手工干预得到的。 Given a specific domain and problem,automated planning will generate plan solutions composed of applicable actions. In classic planning,actions have deterministic effects and are carried out sequentially. However,in real-world problems,the effects of an action might be non-deterministic and there might be concurrent actions. Therefore,the parallel and probabilistic planning( PPP) was proposed. The PPP has a strong application perspective and is drawing a great deal of attention in the planning community. Therefore,this paper presented a survey on the PPP. It first gave formal definitions of domains,problems and plan solutions of the PPP. Then it introduced competition languages,benchmark domains and competitive planners in the PPP. Finally,it tested two representative planners. Experiment results show that,for the efficiency,the results were similar to those in the competitions. However,the scalability was different. It might be caused by some unpublished source codes or some manual intervention.
出处 《计算机应用研究》 CSCD 北大核心 2016年第6期1607-1611,共5页 Application Research of Computers
基金 中央高校基本科研业务费专项资金资助项目(21615438) 广州市云计算安全与测评技术重点实验室开放基金资助项目(GZCSKL-1408)
关键词 自动规划 并行概率规划 国际规划比赛 规划领域 规划器 automated planning parallel and probabilistic planning(PPP) international planning competitions(IPCs) planning domains planners
  • 相关文献

参考文献32

  • 1Geffner H,Bonet B.A concise introduction to models and methods for automated planning[M] //Synthesis Lectures on Artificial Intelligence and Machine Learning.[S.l.] :Morgan & Claypool Publishers,2013:1-141.
  • 2Ghallab M,Nau D,Traverso P.Automated planning:theory and practice[M].San Francisco:Morgan Kauffmann Publishers,2004:1-635.
  • 3Ghallab M,Nau D,Traverso P.自动规划--理论和实践[M].姜云飞,杨强,凌应标,译.北京:清华大学出版社,2008.
  • 4Piacentini C,Alimisis V,Fox M,et al.An extension of metric temporal planning with application to AC voltage control[J].Artificial Intelligence,2015,229(12):210-245.
  • 5Núez S,Borrajo D,López C L.Automatic construction of optimal static sequential portfolios for AI planning and beyond[J].Artificial Intelligence,2015,226(9):75-101.
  • 6Brafman R,Domshlak C.On the complexity of planning for agent teams and its implications for single agent[J].Artificial Intelligence,2013,198(5):52-71.
  • 7Hanheide M,Gbelbecker M,Horn G,et al.Robot task planning and explanation in open and uncertain worlds[J].Artificial Intelligence,2015(In Press).
  • 8饶东宁,蒋志华,姜云飞,吴康恒.从WSBPEL程序中学习Web服务的不确定动作模型[J].计算机研究与发展,2010,47(3):445-454. 被引量:10
  • 9Milani A,Terragnolo M.Representing conflicts in parallel planning[C] //Proc of the 1st International Conference on Artificial Intelligence Planning Systems.San Francisco:Morgan Kauffmann Publishers,1992:291-292.
  • 10Cimatti A,Roveri M,Traverso P.Strong planning in non-deterministic domain via model checking[C] //Proc of the 4th International Conference on AI Planning System.Palo Alto:AAAI Press,1998:36-43.

二级参考文献18

  • 1史玉良,黄光安,叶炜,张亮,施伯乐.基于任务依赖信息的Web服务自动合成[J].计算机研究与发展,2006,43(12):2110-2116. 被引量:8
  • 2邱莉榕,史忠植,林芬,常亮.基于主体的语义Web服务自动组合研究[J].计算机研究与发展,2007,44(4):643-650. 被引量:27
  • 3赖志锋,姜云飞.智能规划中基于遗传算法的动作模型学习[J].计算机学报,2007,30(6):945-953. 被引量:6
  • 4IBM, Microsoft, BEA. Web services business process execution language-version 1 [OL]. [2007-02-08]. http:// www. ibm. com/developerworks/library/specification/ws-bpel/.
  • 5McIlraith S, Fadel R. Planning with complex actions [C]// Proc of the 9th Int Workshop on Non-Monotonic Reasoning (NMR2002). Menlo Park: AAAI, 2002:356-364.
  • 6Rao D G, Jiang Z H, Jiang Y F. Fault tolerant, Web services composition as planning [C] //Proc of the 2007 Int Conf on Intelligent Systems and Knowledge Engineering (1SKE2007). Paris: Atlantis, 2007 [2007-11-01]. doi: 10. 2991/iske. 2007.93.
  • 7Yang Q, Wu K H, Jiang Y F. Learning action models from plan examples using weighted MAX-SAT [J]. Artificial Intelligence, 2007, 171(2/3):107-143.
  • 8Sirin E, Parsia B, Wu D, et al. HTN planning for Web service composition using SHOP2 [J]. Journal of Web Semantics, 2004, 1(4), 377-396.
  • 9Traverso P, Pistore M. Automated composition of semantic Web services into executable processes [C] //Proc of the 3rd Int Semantic Web Conf (1SWC'04). Berlin: Springer, 2004: 380-394.
  • 10Pistore M, Traverso P, Bertoli P. Automated composition of Web services by planning in asynchronous domains [C]// Proc of the 15th Int Conf on Automated Planning Scheduling (ICAPS'05). Menlo Park: AAAI, 2005:2-11.

共引文献9

同被引文献10

引证文献3

二级引证文献8

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部