Revisiting neighborhood inverse consistency on binary CSPs

Authors:
Robert J. Woodward;Shant Karakashian;Berthe Y. Choueiry;Christian Bessiere
Affiliations:
Constraint Systems Laboratory, University of Nebraska-Lincoln;Constraint Systems Laboratory, University of Nebraska-Lincoln;Constraint Systems Laboratory, University of Nebraska-Lincoln;LIRMM-CNRS, University of Montpellier, France
Venue:
CP'12 Proceedings of the 18th international conference on Principles and Practice of Constraint Programming
Year:
2012

Citing 8
Cited 0

A Sufficient Condition for Backtrack-Free Search

Journal of the ACM (JACM)
Binary vs. non-binary constraints

Artificial Intelligence
Constraint Processing

Constraint Processing
Algorithmic Graph Theory and Perfect Graphs (Annals of Discrete Mathematics, Vol 57)

Algorithmic Graph Theory and Perfect Graphs (Annals of Discrete Mathematics, Vol 57)
Conservative dual consistency

AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Domain filtering consistencies

Journal of Artificial Intelligence Research
Neighborhood inverse consistency preprocessing

AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Second-order consistencies

Journal of Artificial Intelligence Research

Quantified Score

Hi-index	0.00

Visualization

Abstract

Our goal is to investigate the definition and application of strong consistency properties on the dual graphs of binary Constraint Satisfaction Problems (CSPs). As a first step in that direction, we study the structure of the dual graph of binary CSPs, and show how it can be arranged in a triangle-shaped grid. We then study, in this context, Relational Neighborhood Inverse Consistency (RNIC), which is a consistency property that we had introduced for non-binary CSPs [17]. We discuss how the structure of the dual graph of binary CSPs affects the consistency level enforced by RNIC. Then, we compare, both theoretically and empirically, RNIC to Neighborhood Inverse Consistency (NIC) and strong Conservative Dual Consistency (sCDC), which are higher-level consistency properties useful for solving difficult problem instances. We show that all three properties are pairwise incomparable.