ARC-CONSISTENCY AND ARC-CONSISTENCY AGAIN

被引:123
作者
BESSIERE, C
机构
[1] LIRMM, University of Montpellier II, 34392 Montpellier Cedex 5, 161, rue Ada
关键词
D O I
10.1016/0004-3702(94)90041-8
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
There is no need to show the importance of arc-consistency in constraint networks. Mohr and Henderson [9] have proposed AC-4, an algorithm with optimal worst-case time complexity. But it has two drawbacks: its space complexity and average time complexity. In problems with many solutions, where constraints are large, these drawbacks become so important that users often replace AC-4 by AC-3 [8], a non-optimal algorithm. In this paper, we propose a new algorithm, AC-6, which keeps the optimal worst-case time complexity of AC-4 while working out the drawback of space complexity. Moreover, the average time complexity of AC-6 is optimal for constraint networks where nothing is known about the constraint semantics.
引用
收藏
页码:179 / 190
页数:12
相关论文
共 19 条
[1]  
BESSIERE C, 1993, PROCEEDINGS OF THE ELEVENTH NATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, P108
[2]  
BESSIERE C, 1991, PROCEEDINGS : NINTH NATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOLS 1 AND 2, P221
[3]   ENHANCEMENT SCHEMES FOR CONSTRAINT PROCESSING - BACKJUMPING, LEARNING, AND CUTSET DECOMPOSITION [J].
DECHTER, R .
ARTIFICIAL INTELLIGENCE, 1990, 41 (03) :273-312
[4]   INCREASING TREE-SEARCH EFFICIENCY FOR CONSTRAINT SATISFACTION PROBLEMS [J].
HARALICK, RM ;
ELLIOTT, GL .
ARTIFICIAL INTELLIGENCE, 1980, 14 (03) :263-313
[5]  
JANSSEN P, 1990, NEW J CHEM, V14, P969
[6]   CONSISTENCY IN NETWORKS OF RELATIONS [J].
MACKWORTH, AK .
ARTIFICIAL INTELLIGENCE, 1977, 8 (01) :99-118
[7]   THE COMPLEXITY OF SOME POLYNOMIAL NETWORK CONSISTENCY ALGORITHMS FOR CONSTRAINT SATISFACTION PROBLEMS [J].
MACKWORTH, AK ;
FREUDER, EC .
ARTIFICIAL INTELLIGENCE, 1985, 25 (01) :65-74
[8]   ARC AND PATH CONSISTENCY REVISITED [J].
MOHR, R ;
HENDERSON, TC .
ARTIFICIAL INTELLIGENCE, 1986, 28 (02) :225-233
[9]  
Mohr R., 1988, Syntactic and Structural Pattern Recognition. Proceedings of the NATO Advanced Research Workshop, P217
[10]   NETWORKS OF CONSTRAINTS - FUNDAMENTAL PROPERTIES AND APPLICATIONS TO PICTURE PROCESSING [J].
MONTANAR.U .
INFORMATION SCIENCES, 1974, 7 (02) :95-132