Evidential Reasoning with Conditional Belief Functions
Artificial Intelligence
2013-02-28 v1
Abstract
In the existing evidential networks with belief functions, the relations among the variables are always represented by joint belief functions on the product space of the involved variables. In this paper, we use conditional belief functions to represent such relations in the network and show some relations of these two kinds of representations. We also present a propagation algorithm for such networks. By analyzing the properties of some special evidential networks with conditional belief functions, we show that the reasoning process can be simplified in such kinds of networks.
Cite
@article{arxiv.1302.6854,
title = {Evidential Reasoning with Conditional Belief Functions},
author = {Hong Xu and Philippe Smets},
journal= {arXiv preprint arXiv:1302.6854},
year = {2013}
}
Comments
Appears in Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence (UAI1994)