Computing Probability Intervals Under Independency Constraints
Artificial Intelligence
2013-04-05 v1
Abstract
Many AI researchers argue that probability theory is only capable of dealing with uncertainty in situations where a full specification of a joint probability distribution is available, and conclude that it is not suitable for application in knowledge-based systems. Probability intervals, however, constitute a means for expressing incompleteness of information. We present a method for computing such probability intervals for probabilities of interest from a partial specification of a joint probability distribution. Our method improves on earlier approaches by allowing for independency relationships between statistical variables to be exploited.
Cite
@article{arxiv.1304.1140,
title = {Computing Probability Intervals Under Independency Constraints},
author = {Linda C. van der Gaag},
journal= {arXiv preprint arXiv:1304.1140},
year = {2013}
}
Comments
Appears in Proceedings of the Sixth Conference on Uncertainty in Artificial Intelligence (UAI1990)