The complexity of conservative valued CSPs Conference Paper


Author(s): Kolmogorov, Vladimir; Živný, Stanislav
Title: The complexity of conservative valued CSPs
Affiliation
Abstract: We study the complexity of valued constraint satisfaction problems (VCSP). A problem from VCSP is characterised by a constraint language, a fixed set of cost functions over a finite domain. An instance of the problem is specified by a sum of cost functions from the language and the goal is to minimise the sum. Under the unique games conjecture, the approximability of finite-valued VCSPs is well-understood, see Raghavendra [FOCS’08]. However, there is no characterisation of finite-valued VCSPs, let alone general-valued VCSPs, that can be solved exactly in polynomial time, thus giving insights from a combinatorial optimisation perspective. We consider the case of languages containing all possible unary cost functions. In the case of languages consisting of only {0, ∞}-valued cost functions (i.e. relations), such languages have been called conservative and studied by Bulatov [LICS’03] and recently by Barto [LICS’11]. Since we study valued languages, we call a language conservative if it contains all finite-valued unary cost functions. The computational complexity of conservative valued languages has been studied by Cohen et al. [AIJ’06] for languages over Boolean domains, by Deineko et al. [JACM’08] for {0,1}-valued languages (a.k.a Max-CSP), and by Takhanov [STACS’10] for {0,∞}-valued languages containing all finite- valued unary cost functions (a.k.a. Min-Cost-Hom). We prove a Schaefer-like dichotomy theorem for conservative valued languages: if all cost functions in the language satisfy a certain condition (specified by a complementary combination of STP and MJN multimorphisms), then any instance can be solved in polynomial time (via a new algorithm developed in this paper), otherwise the language is NP-hard. This is the first complete complexity classification of general-valued constraint languages over non-Boolean domains. It is a common phenomenon that complexity classifications of problems over non-Boolean domains is significantly harder than the Boolean case. The polynomial-time algorithm we present for the tractable cases is a generalisation of the submodular minimisation problem and a result of Cohen et al. [TCS’08]. Our results generalise previous results by Takhanov [STACS’10] and (a subset of results) by Cohen et al. [AIJ’06] and Deineko et al. [JACM’08]. Moreover, our results do not rely on any computer-assisted search as in Deineko et al. [JACM’08], and provide a powerful tool for proving hardness of finite-valued and general-valued languages.
Keywords: Polynomial-time; Approximability; Boolean domain; Computer assisted; Constraint language; Dichotomy theorem; Finite domains; Generalisation; MAX-CSP; NP-hard; Polynomial-time algorithms; Submodular; Unique games conjecture; Valued constraint satisfaction problems
Conference Title: SODA: Symposium on Discrete Algorithms
Conference Dates: January 17-19, 2012
Conference Location: Kyoto, Japan
ISBN: 1557-9468
Publisher: SIAM  
Date Published: 2012-01-01
Start Page: 750
End Page: 759
Sponsor: Vladimir Kolmogorov is supported by the Royal Academy of Eng ineering/EPSRC.
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Open access: yes (repository)
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