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    題名: Advances in applying stochastic-dominance relationships to bounding probability distributions in Bayesian networks
    作者: 劉昭麟
    Liu, Chao-Lin
    貢獻者: IASTED
    國立政治大學資訊科學系
    關鍵詞: stochastic-dominance relationships;bounding probability distributions;Bayesian networks
    日期: 2002-09
    上傳時間: 2010-05-27 16:48:38 (UTC+8)
    摘要: Bounds of probability distributions are useful for many reasoning tasks, including resolving the qualitative ambi- guities in qualitative probabilistic networks and search- ing the best path in stochastic transportation networks. This paper investigates a subclass of the state-space ab- straction methods that are designed to approximately evaluate Bayesian networks. Taking advantage of par- ticular stochastic-dominance relationships among ran- dom variables, these special methods aggregate states of random variables to obtain bounds of probability dis- tributions at much reduced computational costs, thereby achieving high responsiveness of the overall system. The existing methods demonstrate two drawbacks, however. The strict reliance on the particular stochastic- dominance relationships confines their applicability. Also, designed for general Bayesian networks, these methods might not achieve their best performance in spe- cial domains, such as fastest-path planning problems. The author elaborates on these problems, and offers ex- tensions to improve the existing approximation tech- niques.
    關聯: Proceedings of the IASTED International Conference on Artificial and Computational Intelligence 2002
    資料類型: conference
    顯示於類別:[資訊科學系] 會議論文

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