Improving the Performance of Consistency Algorithms by Localizing and Bolstering Propagation in a Tree Decomposition

Authors

  • Shant Karakashian University of Nebraska-Lincoln
  • Robert Woodward University of Nebraska-Lincoln
  • Berthe Choueiry University of Nebraska-Lincoln

DOI:

https://doi.org/10.1609/aaai.v27i1.8594

Keywords:

Constraint satisfaction, CSP, consistency property, constraint propagation, tree decomposition, relational consistency

Abstract

The tractability of a Constraint Satisfaction Problem (CSP)is guaranteed by a direct relationship between its consistencylevel and a structural parameter of its constraint network suchas the treewidth. This result is not widely exploited in practicebecause enforcing higher-level consistencies can be costlyand can change the structure of the constraint network andincrease its width. Recently, R(*,m)C was proposed as a relational consistency property that does not modify the structureof the graph and, thus, does not affect its width. In this paper,we explore two main strategies, based on a tree decomposition of the CSP, for improving the performance of enforcingR(*,m)C and getting closer to the above tractability condition. Those strategies are: a) localizing the application ofthe consistency algorithm to the clusters of the tree decomposition, and b) bolstering constraint propagation betweenclusters by adding redundant constraints at their separators,for which we propose three new schemes. We characterizethe resulting consistency properties by comparing them, theoretically and empirically, to the original R(*,m)C and thepopular GAC and maxRPWC, and establish the benefits ofour approach for solving difficult problems.

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Published

2013-06-30

How to Cite

Karakashian, S., Woodward, R., & Choueiry, B. (2013). Improving the Performance of Consistency Algorithms by Localizing and Bolstering Propagation in a Tree Decomposition. Proceedings of the AAAI Conference on Artificial Intelligence, 27(1), 466-473. https://doi.org/10.1609/aaai.v27i1.8594