A review of explanation methods for Bayesian networks

被引：125

作者：

Lacave, C

Díez, FJ

机构：

[1] Univ Castilla La Mancha, Dept Comp Sci, E-13071 Ciudad Real, Spain

[2] Univ Nacl Educ Distancia, Dept Artificial Intelligence, Madrid 28040, Spain

来源：

KNOWLEDGE ENGINEERING REVIEW | 2002年 / 17卷 / 02期

关键词：

D O I：

10.1017/S026988890200019X

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

One of the key factors for the acceptance of expert systems in real-world domains is the ability to explain their reasoning (Buchanan & Shortliffe, 1984; Henrion & Druzdzel, 1990). This paper describes the basic properties that characterise explanation methods and reviews the methods developed to date for explanation in Bayesian networks.

引用

页码：107 / 127

页数：21

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