Title : 
A Dichotomy Theorem for the Resolution Complexity of Random Constraint Satisfaction Problems
         
        
            Author : 
Chan, Siu On ; Molloy, Michael
         
        
            Author_Institution : 
Dept. of Comput. Sci., Univ. of Toronto, Toronto, ON
         
        
        
        
        
            Abstract : 
We consider random instances of constraint satisfaction problems where each variable has domain size O(1), each constraint is on O(1) variables and the constraints are chosen from a specified distribution. The number of constraints is cn where c is a constant. We prove that for every possible distribution, either the resolution complexity is almost surely polylogarithmic for sufficiently large c, or it is almost surely exponential for every c > 0. We characterize the distributions of each type. To do so, we introduce a closure operation on a set of constraints which yields the set of all constraints that, in some sense, appear implicitly in the random CSP.
         
        
            Keywords : 
computational complexity; constraint theory; operations research; dichotomy theorem; random constraint satisfaction problems; resolution complexity; Computer science; Constraint theory; H infinity control; Polynomials; Davis-Putnam algorithms; random constraint satisfaction problems; random walks; resolution complexity;
         
        
        
        
            Conference_Titel : 
Foundations of Computer Science, 2008. FOCS '08. IEEE 49th Annual IEEE Symposium on
         
        
            Conference_Location : 
Philadelphia, PA
         
        
        
            Print_ISBN : 
978-0-7695-3436-7
         
        
        
            DOI : 
10.1109/FOCS.2008.70