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I. Kanj, St. Szeider:
"On the Subexponential Time Complexity of CSP";
Vortrag: AAAI Conference, Bellevue, WA, USA; 14.07.2013 - 18.07.2013; in: "Proceedings of the 27th AAAI Conference on Artificial Intelligence (AAAI´13)", M. desJardins, M. Littman (Hrg.); AAAI Press, (2013), ISBN: 978-1-57735-615-8; S. 459 - 465.

A Constraint Satisfaction Problem (CSP) with n variables ranging over a domain of d values can be solved by brute-force in dn 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.

http://publik.tuwien.ac.at/files/PubDat_223483.pdf

Projektleitung Stefan Szeider:
The Parameterized Complexity of Reasoning Problems