We study the approximability of the MAX k-CSP problem over non-boolean domains, more specifically over {0,1,...,q - 1} for some integer q. We extend the techniques of Samorodnitsky and Trevisan [19] to obtain a UGC hardness result when q is a prime. More precisely, assuming the Unique Games Conjecture, we show that it is NP-hard to approximate the problem to a ratio greater than q 2 k/q k . Independent of this work, Austrin and Mossel [2] obtain a more general UGC hardness result using entirely different techniques. We also obtain an approximation algorithm that achieves a ratio of C(q) •k/q k for some constant C(q) depending only on q, via a subroutine for approximating the value of a semidefinite quadratic form when the variables take values on the corners of the q-dimensional simplex. This generalizes an algorithm of Nesterov [16] for the ±1-valued variables. It has been pointed out to us [15] that a similar approximation ratio can be obtained by reducing the non-boolean case to a boolean CSP. © 2008 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Guruswami, V., & Raghavendra, P. (2008). Constraint satisfaction over a non-boolean domain: Approximation algorithms and unique-games hardness. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5171 LNCS, pp. 77–90). https://doi.org/10.1007/978-3-540-85363-3_7
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