Robust Approximation of Temporal CSP

Authors Suguru Tamaki, Yuichi Yoshida

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Suguru Tamaki
Yuichi Yoshida

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Suguru Tamaki and Yuichi Yoshida. Robust Approximation of Temporal CSP. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2014). Leibniz International Proceedings in Informatics (LIPIcs), Volume 28, pp. 419-432, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)


A temporal constraint language G is a set of relations with first-order definitions in (Q; <). Let CSP(G) denote the set of constraint satisfaction problem instances with relations from G. CSP(G) admits robust approximation if, for any e >= 0, given a (1-e)-satisfiable instance of CSP(G), we can compute an assignment that satisfies at least a (1-f(e))-fraction of constraints in polynomial time. Here, f(e) is some function satisfying f(0)=0 and f(e) goes 0 as e goes 0. Firstly, we give a qualitative characterization of robust approximability: Assuming the Unique Games Conjecture, we give a necessary and sufficient condition on G under which CSP(G) admits robust approximation. Secondly, we give a quantitative characterization of robust approximability: Assuming the Unique Games Conjecture, we precisely characterize how f(e) depends on e for each G. We show that our robust approximation algorithms can be run in almost linear time.
  • constraint satisfaction
  • maximum satisfiability
  • approximation algorithm
  • hardness of approximation
  • infinite domain


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