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題名 Bounding probabilistic relationships in Bayesian networks using qualitative influences: methods and applications
作者 Liu, Chao-lin
劉昭麟
Wellman, Michael P.
貢獻者 資科系
日期 2004
上傳時間 17-Jun-2015 15:08:50 (UTC+8)
摘要 We present conditions under which one can bound the probabilistic relationships between random variables in a Bayesian network by exploiting known or induced qualitative relationships. Generic strengthening and weakening operations produce bounds on cumulative distributions, and the directions of these bounds are maintained through qualitative influences. We show how to incorporate these operations in a state-space abstraction method, so that bounds provably tighten as an approximate network is refined. We apply these techniques to qualitative tradeoff resolution demonstrating an ability to identify qualitative relationships among random variables without exhaustively using the probabilistic information encoded in the given network. In an application to path planning, we present an anytime algorithm with run-time computable error bounds.
關聯 International Journal of Approximate Reasoning - IJAR , vol. 36, no. 1, pp. 31-73
資料類型 article
DOI http://dx.doi.org/10.1016/j.ijar.2003.06.002
dc.contributor 資科系-
dc.creator (作者) Liu, Chao-lin-
dc.creator (作者) 劉昭麟zh_TW
dc.creator (作者) Wellman, Michael P.en_US
dc.date (日期) 2004-
dc.date.accessioned 17-Jun-2015 15:08:50 (UTC+8)-
dc.date.available 17-Jun-2015 15:08:50 (UTC+8)-
dc.date.issued (上傳時間) 17-Jun-2015 15:08:50 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/75891-
dc.description.abstract (摘要) We present conditions under which one can bound the probabilistic relationships between random variables in a Bayesian network by exploiting known or induced qualitative relationships. Generic strengthening and weakening operations produce bounds on cumulative distributions, and the directions of these bounds are maintained through qualitative influences. We show how to incorporate these operations in a state-space abstraction method, so that bounds provably tighten as an approximate network is refined. We apply these techniques to qualitative tradeoff resolution demonstrating an ability to identify qualitative relationships among random variables without exhaustively using the probabilistic information encoded in the given network. In an application to path planning, we present an anytime algorithm with run-time computable error bounds.-
dc.format.extent 449247 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) International Journal of Approximate Reasoning - IJAR , vol. 36, no. 1, pp. 31-73-
dc.title (題名) Bounding probabilistic relationships in Bayesian networks using qualitative influences: methods and applications-
dc.type (資料類型) articleen
dc.identifier.doi (DOI) 10.1016/j.ijar.2003.06.002-
dc.doi.uri (DOI) http://dx.doi.org/10.1016/j.ijar.2003.06.002-