AAAI Publications, Twenty-Seventh AAAI Conference on Artificial Intelligence

Font Size: 
On the Subexponential Time Complexity of CSP
Iyad Kanj, Stefan Szeider

Last modified: 2013-06-30


A Constraint Satisfaction Problem (CSP) with n variables ranging over a domain of d values can be solved by brute-force in d^n steps (omitting a polynomial factor). With a more careful approach, this trivial upper bound can be improved for certain natural restrictions of the CSP. In this paper we establish theoretical limits to such improvements, and draw a detailed landscape of the subexponential-time complexity of CSP. We first establish relations between the subexponential-time complexity of CSP and that of other problems, including CNF-Sat. We exploit this connection to provide tight characterizations of the subexponential-time complexity of CSP under common assumptions in complexity theory. For several natural CSP parameters, we obtain threshold functions that precisely dictate the subexponential-time complexity of CSP with respect to the parameters under consideration. Our analysis provides fundamental results indicating whether and when one can significantly improve on the brute-force search approach for solving CSP.


Constraint Satisfaction; Subexponential Time; Exponential Time Hypothesis; Treewidth

Full Text: PDF