Probabilistic Arc Consistency: A Connection Between Constraint Reasoning and Probabilistic Reasoning
Abstract
We document a connection between constraint reasoning and probabilistic reasoning. We present an algorithm, called probabilistic arc consistency, which is both a generalization of a well known algorithm for arc consistency used in constraint reasoning, and a specialization of the belief updating algorithm for singly-connected networks. Our algorithm is exact for singlyconnected constraint problems, but can work well as an approximation for arbitrary problems. We briefly discuss some empirical results, and related methods.
Cite
Text
Horsch and Havens. "Probabilistic Arc Consistency: A Connection Between Constraint Reasoning and Probabilistic Reasoning." Conference on Uncertainty in Artificial Intelligence, 2000.Markdown
[Horsch and Havens. "Probabilistic Arc Consistency: A Connection Between Constraint Reasoning and Probabilistic Reasoning." Conference on Uncertainty in Artificial Intelligence, 2000.](https://mlanthology.org/uai/2000/horsch2000uai-probabilistic/)BibTeX
@inproceedings{horsch2000uai-probabilistic,
title = {{Probabilistic Arc Consistency: A Connection Between Constraint Reasoning and Probabilistic Reasoning}},
author = {Horsch, Michael C. and Havens, William S.},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {2000},
pages = {282-290},
url = {https://mlanthology.org/uai/2000/horsch2000uai-probabilistic/}
}