A causal mapping approach to constructing Bayesian networks

被引：185

作者：

Nadkarni, S ^{[1
]}

Shenoy, PP

机构：

[1] Univ Nebraska, Coll Business Adm, Dept Management, Lincoln, NE 68588 USA

[2] Univ Kansas, Sch Business, Lawrence, KS 66045 USA

来源：

DECISION SUPPORT SYSTEMS | 2004年 / 38卷 / 02期

关键词：

causal maps; cognitive maps; Bayesian networks; Bayesian causal maps;

D O I：

10.1016/s0167-9236(03)00095-2

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper describes a systematic procedure for constructing Bayesian networks (BNs) from domain knowledge of experts using the causal mapping approach. We outline how causal knowledge of experts can be represented as causal maps, and how the graphical structure of causal maps can be modified to construct Bayes nets. Probability encoding techniques can be used to assess the numerical parameters of the resulting Bayes nets. We illustrate the construction of a Bayes net starting from a causal map of a systems analyst in the context of an information technology application outsourcing decision. (C) 2003 Elsevier B.V. All rights reserved.

引用

页码：259 / 281

页数：23