A review of explanation methods for Bayesian networks

被引：123
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.
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页码：107 / 127
页数：21
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