Modeling time-varying uncertain situations using Dynamic Influence Nets

被引：28

作者：

Haider, Sajjad ^{[1
]}

Levis, Alexander H. ^{[1
]}

机构：

[1] George Mason Univ, Syst Architectures Lab, Fairfax, VA 22030 USA

来源：

INTERNATIONAL JOURNAL OF APPROXIMATE REASONING | 2008年 / 49卷 / 02期

关键词：

Timed Influence Nets; Dynamic Influence Nets; Dynamic Bayesian Networks; Probabilistic reasoning;

D O I：

10.1016/j.ijar.2008.04.007

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 enhances the Timed Influence Nets (TIN) based formalism to model uncertainty in dynamic situations. The enhancements enable a system modeler to specify persistence and time-varying influences in a dynamic situation that the existing TIN fails to capture. The new class of models is named Dynamic Influence Nets (DIN). Both TIN and DIN provide an alternative easy-to-read and compact representation to several time-based probabilistic reasoning paradigms including Dynamic Bayesian Networks. The Influence Net (IN) based approach has its origin in the Discrete Event Systems modeling. The time delays on arcs and nodes represent the communication and processing delays, respectively, while the changes in the probability of an event at different time instants capture the uncertainty associated with the occurrence of the event over a period of time. (C) 2008 Elsevier Inc. All rights reserved.

引用

页码：488 / 502

页数：15