Authors:
Zineb Habbas
1
;
Kamal Amroun
1
and
Daniel Singer
2
Affiliations:
1
University Paul-Verlaine of Metz and University of Bejaia, France
;
2
University Paul-Verlaine of Metz, France
Keyword(s):
CSP, Dual backtracking, Forward-checking, Hypertree decomposition, Structural decomposition, Ordering Heuristics.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Constraint Satisfaction
;
Symbolic Systems
Abstract:
Solving a CSP (Constraint Satisfaction Problem) is NP-Complete in general. However, there are various classes of CSPs that can be solved in polynomial time. Some of them can be identified by analyzing their structure. It is theoretically well established that a tree (or hypertree) structured CSP can be solved in a backtrack-free way leading to tractability. Different methods exist for converting CSPs in a tree (or hypertree) structured representation. Among these methods Hypertree Decomposition has been proved to be the most general one for non-binary CSPs. Unfortunately, in spite of its good theoretical bound, the unique algorithm for solving CSP from its hypertree structure is inefficient in practice due to its memory explosion. To overcome this problem, we propose in this paper a new approach exploiting a Generalized Hypertree Decomposition. We present the so called HD DBT algorithm (Dual BackTracking algorithm guided by an order induced by a generalized Hypertree Decomposition).
Different heuristics and implementations are presented showing its practical interest.
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