Lazy inference in multiply sectioned Bayesian networks using linked junction forests

被引：0

作者：

Xiang, Yang ^{[1
]}

Chen, Xiaoyun ^{[1
]}

机构：

[1] Univ Guelph, Guelph, ON N1G 2W1, Canada

来源：

ADVANCES IN PROBABILISTIC GRAPHICAL MODELS | 2007年 / 213卷

基金：

加拿大自然科学与工程研究理事会;

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Lazy propagation reduces the space complexity from HUGIN inference. Multiply Sectioned Bayesian Networks extend Bayesian Networks a cooperative multiagent paradigm. To combine the benefits of the two, a framework was proposed earlier to apply lazy propagation to inference in MSBNs. We propose an alternative framework with a simpler compiled structure. The issues of lazy communication and observation entering in a multiagent setting are considered. We prove that the inference is exact.

引用

页码：175 / +

页数：2

共 50 条

[31] Using junction trees for structural learning of Bayesian networks
Zhu, Mingmin
Liu, Sanyang
Yang, Youlong
Liu, Kui
JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS, 2012, 23 (02) : 286 - 292
[32] Temporal-Attribute Inference Using Dynamic Bayesian Networks
Idan, Lihi
COMPUTATIONAL SCIENCE, ICCS 2022, PT II, 2022, : 638 - 652
[33] THE INFERENCE OF HUMAN RESOURCE PLANNING OPERATION USING BAYESIAN NETWORKS
Kataoka, Takayuki
Kanezashi, Masakazu
Morikawa, Katsumi
Takahashi, Katsuhiko
ICIM 2010: PROCEEDINGS OF THE TENTH INTERNATIONAL CONFERENCE ON INDUSTRIAL MANAGEMENT, 2010, : 537 - +
[34] Partial abductive inference in Bayesian networks by using probability trees
de Campos, LM
Gámez, JA
Moral, S
ENTERPRISE INFORMATION SYSTEMS V, 2004, : 146 - 154
[35] Approximate inference in Bayesian networks using binary probability trees
Cano, Andres
Gomez-Olmedo, Manuel
Moral, Serafin
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 2011, 52 (01) : 49 - 62
[36] Fast Bayesian inference for gene regulatory networks using ScanBMA
Young, William Chad
Raftery, Adrian E.
Yeung, Ka Yee
BMC SYSTEMS BIOLOGY, 2014, 8
[37] Inference of distillation column products quality using Bayesian networks
Barbosa, CH
Melo, B
Vellasco, M
Pacheco, M
Vasconcellos, LP
PROCEEDING OF THE 2002 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-3, 2002, : 86 - 91
[38] Bayesian Inference for Reliability of Systems and Networks Using the Survival Signature
Aslett, Louis J. M.
Coolen, Frank P. A.
Wilson, Simon P.
RISK ANALYSIS, 2015, 35 (09) : 1640 - 1651
[39] FECG extraction using Bayesian inference and neural networks approximation
Yin, Ying
Ye, Mao
Ren, Dongxiao
Zhu, Yuanxiang
Yang, Chenxue
Journal of Computational Information Systems, 2010, 6 (06): : 1769 - 1778
[40] Robust inference of Bayesian networks using speciated evolution and ensemble
Kim, KJ
Yoo, JO
Cho, SB
FOUNDATIONS OF INTELLIGENT SYSTEMS, PROCEEDINGS, 2005, 3488 : 92 - 101

← 1 2 3 4 5 →