A modified simulation scheme for inference in Bayesian networks

被引：15

作者：

Bouckaert, RR ^{[1
]}

Castillo, E ^{[1
]}

Gutierrez, JM ^{[1
]}

机构：

[1] UNIV CANTABRIA,E-39005 SANTANDER,SPAIN

来源：

INTERNATIONAL JOURNAL OF APPROXIMATE REASONING | 1996年 / 14卷 / 01期

关键词：

Bayesian networks; simulation; stratified simulation;

D O I：

10.1016/0888-613X(95)00114-V

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We introduce an approximation method for uncertainty propagation based on a modification of the stratified simulation. The method uses a deterministic or perfect sample and calculates the number of times simulated instantiations are selected, avoiding the repetition of identical instantiations which occurs in the standard stratified simulation method. A theoretical analysis is presented to evaluate the performance of the method in comparison with the stratified simulation scheme. The analysis gives a technique to select the required step for the estimation of probabilities with a given error. Some experimental studies compare the proposed with other simulation methods and show a large performance improvement in computation time as well as in simulation errors.

引用

页码：55 / 80

页数：26

共 18 条

[1]

BOUCKAERT R, 1994, 10TH P C UNC ART INT, P102

[2]

BOUCKAERT R, 1994, 10TH P C UNC ART INT, P110

[3]

CASTILLO EF, 1995, 11TH P C UNC ART INT, P55

[4]

Chang K., 1990, UNCERTAINTY ARTIFICI