Variable Elimination in Binary CSP via Forbidden Patterns
Abstract
A variable elimination rule allows the polynomial-time identification of certain variables whose elimination does not affect the satisfiability of an instance. Variable elimination in the constraint satisfaction problem (CSP) can be used in preprocessing or during search to reduce search space size. We show that there are essentially just four variable elimination rules defined by forbidding generic sub-instances, known as irreducible patterns, in arc-consistent CSP instances. One of these rules is the Broken Triangle Property, whereas the other three are novel.
Cite
Text
Cohen et al. "Variable Elimination in Binary CSP via Forbidden Patterns." International Joint Conference on Artificial Intelligence, 2013.Markdown
[Cohen et al. "Variable Elimination in Binary CSP via Forbidden Patterns." International Joint Conference on Artificial Intelligence, 2013.](https://mlanthology.org/ijcai/2013/cohen2013ijcai-variable/)BibTeX
@inproceedings{cohen2013ijcai-variable,
title = {{Variable Elimination in Binary CSP via Forbidden Patterns}},
author = {Cohen, David A. and Cooper, Martin C. and Escamocher, Guillaume and Zivný, Stanislav},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2013},
pages = {517-523},
url = {https://mlanthology.org/ijcai/2013/cohen2013ijcai-variable/}
}