A comparison of Bayesian and belief function reasoning

被引：49

作者：

Cobb, BR ^{[1
]}

Shenoy, PP ^{[1
]}

机构：

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

来源：

INFORMATION SYSTEMS FRONTIERS | 2003年 / 5卷 / 04期

关键词：

Bayesian networks; Dempster-Shafer belief functions; valuation-based systems;

D O I：

10.1023/B:ISFI.0000005650.63806.03

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The goal of this paper is to compare the similarities and differences between Bayesian and belief function reasoning. Our main conclusion is that although there are obvious differences in semantics, representations, and the rules for combining and marginalizing representations, there are many similarities. We claim that the two calculi have roughly the same expressive power. Each calculus has its own semantics that allow us to construct models suited for these semantics. Once we have a model in either calculus, one can transform it to the other by means of a suitable transformation.

引用

页码：345 / 358

页数：14

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