A Constraint Propagation Approach to Probabilistic Reasoning
Artificial Intelligence
2013-04-15 v1
Abstract
The paper demonstrates that strict adherence to probability theory does not preclude the use of concurrent, self-activated constraint-propagation mechanisms for managing uncertainty. Maintaining local records of sources-of-belief allows both predictive and diagnostic inferences to be activated simultaneously and propagate harmoniously towards a stable equilibrium.
Cite
@article{arxiv.1304.3422,
title = {A Constraint Propagation Approach to Probabilistic Reasoning},
author = {Judea Pearl},
journal= {arXiv preprint arXiv:1304.3422},
year = {2013}
}
Comments
Appears in Proceedings of the First Conference on Uncertainty in Artificial Intelligence (UAI1985)