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https://ah.lib.nccu.edu.tw/handle/140.119/39690
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: | Sep-2002 | 上傳時間: | 27-May-2010 | 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 |
Appears in Collections: | 會議論文 |
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