Application of a hill-climbing algorithm to exact and approximate inference in credal networks

被引：0

作者：

Cano, Andres ^{[1
]}

Gomez, Manuel ^{[1
]}

Moral, Serafin ^{[1
]}

机构：

[1] Univ Granada, Dept Comp Sci & Artificial Intelligence, ETS Ingn Informat, E-18071 Granada, Spain

来源：

ISIPTA 05-PROCEEDINGS OF THE FOURTH INTERNATIONAL SYMPOSIUM ON IMPRECISE PROBABILITIES AND THEIR APPLICATIONS | 2005年

关键词：

Credal network; probability intervals; Bayesian networks; strong independence; hill-climbing; branch-and-bound algorithms;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This paper proposes two new algorithms for inference in credal networks. These algorithms enable probability intervals to be obtained for the states of a given query variable. The first algorithm is approximate and uses the hill-climbing technique in the Shenoy-Shafer architecture to propagate in join trees; the second is exact and is a modification of Rocha and Cozman's branch-and-bound algorithm, but applied to general directed acyclic graphs.

引用

页码：88 / 97

页数：10

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