Domain permutation reduction for constraint satisfaction problems

被引:12
作者
Green, Martin J. [1 ]
Cohen, David A. [1 ]
机构
[1] Univ London, Dept Comp Sci, Egham TW20 0EX, Surrey, England
基金
英国工程与自然科学研究理事会;
关键词
complexity; constraint satisfaction problem; CSP; NP-completeness; renamable horn; stable marriage; tractability;
D O I
10.1016/j.artint.2007.12.001
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper is concerned with the Constraint Satisfaction Problem (CSP). It is well-known that the general CSP is NP-hard. However, there has been significant success in discovering subproblems which are tractable (polynomial time solvable). One of the most effective ways to obtain a tractable subproblem has been to force all of the constraint relations to lie in some tractable language. In this paper we define a new way of identifying tractable subproblems of the CSP Let P be an arbitrary CSP instance and Gamma be any tractable language. Suppose there exists, for each variable of P, a permutation of the domain such the resultant permuted constraint relations of P all lie in Gamma. The domain permuted instance is then an instance of a tractable class and can be solved by the polynomial time algorithm for Gamma. Solutions to P can be obtained by inverting the domain permutations. The question, for a given class of instances and language , whether such a set of domain permutations can be found efficiently is the key to this method's tractability. One of the important contributions made in this paper is the notion of a "lifted constraint instance" which is a powerful tool to study this question. We consider the open problem of discovering domain permutations which make instances max-closed. We show that, for bounded arity instances over a Boolean domain this problem is tractable, while for domain size three it is intractable even for binary instances. We give a simple proof verifying the tractability of discovering domain permutations which make instances row convex. We refute a published result by giving a simple proof of the intractability of discovering domain permutations which make instances, even with domain size four, connected row convex. We demonstrate that triangulated and stable marriage instances are reducible, via domain permutations, to max-closed instances. This provides a simple explanation for arc consistency deciding these instances. We verify with a simple direct proof the tractability of identification of renamable Horn instances, and the intractability of finding the largest renamable Horn subset of clauses of an instance of SAT. We describe natural tractable classes which properly extend the maximal relational classes arising from tractable constraint languages. We believe that domain permutation reductions have a significant chance of being useful in practical applications. (C) 2008 Elsevier B.V. All rights reserved.
引用
收藏
页码:1094 / 1118
页数:25
相关论文
共 50 条
  • [31] Robust Satisfiability of Constraint Satisfaction Problems
    Barto, Libor
    Kozik, Marcin
    STOC'12: PROCEEDINGS OF THE 2012 ACM SYMPOSIUM ON THEORY OF COMPUTING, 2012, : 931 - 940
  • [32] BINARISATION FOR VALUED CONSTRAINT SATISFACTION PROBLEMS
    Cohen, David A.
    Cooper, Martin C.
    Jeavons, Peter G.
    Krokhin, Andrei
    Powell, Robert
    Zivny, Stanislav
    SIAM JOURNAL ON DISCRETE MATHEMATICS, 2017, 31 (04) : 2279 - 2300
  • [33] LOGICAL COMPACTNESS AND CONSTRAINT SATISFACTION PROBLEMS
    Rorabaugh, Danny
    Tardif, Claude
    Wehlau, David
    LOGICAL METHODS IN COMPUTER SCIENCE, 2017, 13 (01)
  • [34] Characterising the complexity of constraint satisfaction problems defined by 2-constraint forbidden patterns
    Cooper, Martin C.
    Escamocher, Guillaume
    DISCRETE APPLIED MATHEMATICS, 2015, 184 : 89 - 113
  • [35] The Complexity of Temporal Constraint Satisfaction Problems
    Bodirsky, Manuel
    Kara, Jan
    STOC'08: PROCEEDINGS OF THE 2008 ACM INTERNATIONAL SYMPOSIUM ON THEORY OF COMPUTING, 2008, : 29 - 38
  • [36] Exploiting the constrainedness in constraint satisfaction problems
    Salido, MA
    Barber, F
    ARTIFICIAL INTELLIGENCE: METHODOLOGY, SYSTEMS, AND APPLICATIONS, PROCEEDINGS, 2004, 3192 : 126 - 136
  • [37] WHEN SYMMETRIES ARE NOT ENOUGH: A HIERARCHY OF HARD CONSTRAINT SATISFACTION PROBLEMS
    Gillibert, Pierre
    Jonusas, Julius
    Kompatscher, Michael
    Mottet, Antoine
    Pinsker, Michael
    SIAM JOURNAL ON COMPUTING, 2022, 51 (02) : 175 - 213
  • [38] Learning variable ordering heuristics for solving Constraint Satisfaction Problems
    Song, Wen
    Cao, Zhiguang
    Zhang, Jie
    Xu, Chi
    Lim, Andrew
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2022, 109
  • [39] Dynamic algorithms for classes of constraint satisfaction problems
    Frigioni, D
    Marchetti-Spaccamela, AT
    Nanni, U
    THEORETICAL COMPUTER SCIENCE, 2001, 259 (1-2) : 287 - 305
  • [40] Perturbed Message Passing for Constraint Satisfaction Problems
    Ravanbakhsh, Siamak
    Greiner, Russell
    JOURNAL OF MACHINE LEARNING RESEARCH, 2015, 16 : 1249 - 1274