The computational structure of monotone monadic SNP and constraint satisfaction: A study through datalog and group theory

被引:689
作者
Feder, T
Vardi, MY
机构
[1] IBM Corp, Almaden Res Ctr, San Jose, CA 95120 USA
[2] Rice Univ, Dept Comp Sci, Houston, TX 77251 USA
关键词
satisfiability; graph coloring; datalog; group theory; linear equations;
D O I
10.1137/S0097539794266766
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
This paper starts with the project of finding a large subclass of NP which exhibits a dichotomy. The approach is to find this subclass via syntactic prescriptions. While the paper does not achieve this goal, it does isolate a class (of problems specified by) "monotone monadic SNP without inequality" which may exhibit this dichotomy. We justify the placing of all these restrictions by showing, essentially using Ladner's theorem, that classes obtained by using only two of the above three restrictions do not show this dichotomy. We then explore the structure of this class. We show that all problems in this class reduce to the seemingly simpler class CSP. We divide CSP into subclasses and try to unify the collection of all known polytime algorithms for CSP problems and extract properties that make CSP problems NP-hard. This is where the second part of the title, "a study through Datalog and group theory," comes in. We present conjectures about this class which would end in showing the dichotomy.
引用
收藏
页码:57 / 104
页数:48
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