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POMDP在战场决策评估中的应用和仿真 被引量：1

Application and Simulation of POMDP in Evaluating Battlefield Decision Making
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摘要 通过将贝叶斯统计方法和POMDP(部分可观测马氏决策过程)方法相结合,采用计算机模拟的方式,预测在给定条件下可能产生的各种作战决策的质量。为解决不确定条件下对决策质量的定量评估提供了一种比较可行的方法。 Through combining Bayes statistical method and POMDP method using computer simulation, the qualities of possible decision makings in specific conditions were prediceed, an appropriate method to quantificationally evaluate decision makings during uncertainty was provided.
作者 王祥 林秀青
机构地区 电子工程学院
出处 《现代防御技术》 北大核心 2008年第1期75-79,共5页 Modern Defence Technology
关键词 部分可观测马氏决策过程 贝叶斯统计方法 决策质量 评估 POMDP hayes statistical method decision making quality assessment
分类号 C934 [经济管理—管理学] E844 [军事—战术学]
作者简介 王祥（1979-），男，四川乐山人。博土生，研究方向为信息作战情报。通信地址：230037安徽省合肥市电子工程学院204室 电话：0551-5766615 E-mail：fenfen8002@163．com
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参考文献5

  • 1Thiebaux S. Anytime State-based Solution Methods for Decision Processes with Non-Markovian Rewards [C]. 18th Conference on Uncertainty in Artificial Intelligence. Edmonton, Canada. 2002:501 -510.
  • 2Poupart P, Boutilier C. Value-directed Belief State Approximation for POMDPs [C] //Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence. San Francisco, USA. Morgan Kaufmann Publishers Inc, 2000 : 497 -506.
  • 3张尧庭 陈汉峰.贝叶斯统计推断[M].北京：科学出版社,1994.193-196.
  • 4Lane T, Kaelbling L. Nearly Deterministic Abstractions of Markov Decision Processes [C] // Eighteenth National Conference on Artificial Intelligence. Edmonton, Canada, 2002:260 -266.
  • 5Poupart P, Boutilier C. Vector-space Analysis of Beliefstate Approximation for POMDPs[C]//Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence. San Francisco, USA : Morgan Kaufmann Publishers Inc, 2001:445 -452.

共引文献19

同被引文献15

  • 1Wang W B,Carr M. A stochastic filtering based data driven approach for residual life prediction and condition based maintenance decision making support[A].2010.1-10.
  • 2Besnard F,Bertling L. An approach for condition-based maintenance optimization applied to wind turbine blades[J].IEEE Trans on Sustainable Energy,2010,(02):77-83.
  • 3胡奇英;刘建庸.马尔可夫决策过程引论[M]西安:西安电子科技大学出版社,2002160-169.
  • 4Grall A,Berenguer C,Dieulle L. A condition-based maintenance policy for stochastically deteriorating systems[J].Reliability Engineering & System Safety,2002,(02):167-180.doi:10.1016/S0951-8320(01)00148-X.
  • 5Ivy J,Pollock S. Marginally monotonic maintenance policies for a multi-state deteriorating machine with probabilistic moni toring and silent failures[J].IEEE Transactions on Reliability,2005,(03):489-497.
  • 6Lin D,Jardine A. Using principal components in a proportional hazards model with application in condition-based maintenance[J].Journal of the Operational Research Society,2006,(08):910-919.
  • 7Ghasemi A,Yacout S,Ouali M S. Optimal condition based maintenance with imperfect information and the proportional hazards model[J].International Journal of Production Research,2007,(04):989-1012.
  • 8A1Durgam M M,Duffuaa S O. Optimal maintenance policies for three-states POMDP with quality measurement errors[A].2010.2239-2243.
  • 9Wang L,Zheng E H,Li Y T. Maintenance optimization of generating equipment based on a condition-based maintenance policy for multi-unit systems[A].2009.2440-2445.
  • 10Atlas L,Ostendorf M,Bernard G D. Hidden Markov models for monitoring machining tool-wear[A].2000.3887-3890.

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现代防御技术
2008年 第1期

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