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The complexity of counting locally maximal satisfying assignments of Boolean CSPs

机译:计算布尔CSP的局部最大满足分配的复杂度

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We investigate the computational complexity of the problem of counting the locally maximal satisfying assignments of a Constraint Satisfaction Problem (CSP) over the Boolean domain {0,1}. A satisfying assignment is locally maximal if any new assignment which is obtained from it by changing a 0 to a 1 is unsatisfying. For each constraint language Gamma,, #LocalMaxCSP(Gamma) denotes the problem of counting the locally maximal satisfying assignments, given an input CSP with constraints in Gamma. We give a complexity dichotomy for the problem of exactly counting the locally maximal satisfying assignments and a complexity trichotomy for the problem of approximately counting them. Relative to the problem #CSP(Gamma), which is the problem of counting all satisfying assignments, the locally maximal version can sometimes be easier but never harder. This finding contrasts with the recent discovery that approximately counting locally maximal independent sets in a bipartite graph is harder (under the usual complexity-theoretic assumptions) than counting all independent sets. (C) 2016 Elsevier B.V. All rights reserved.
机译:我们研究在布尔域{0,1}上计算约束满足问题(CSP)的局部最大满足分配的问题的计算复杂性。如果通过将0更改为1从中获得的任何新分配都不令人满意,则令人满意的分配是局部最大的。对于每种约束语言Gamma,#LocalMaxCSP(Gamma)表示在给定具有Camma约束的输入CSP的情况下计算局部最大满足分配的问题。对于精确计算局部最大满足分配的问题,我们给出了复杂性二分法,对于近似计数它们的问题,我们给出了复杂性三分法。相对于#CSP(Gamma)这个问题,即计算所有令人满意的分配的问题,局部最大版本有时更容易,但从不更难。这一发现与最近的发现形成了鲜明对比,后者发现在二部图中近似计算局部最大独立集(在通常的复杂性理论假设下)比对所有独立集进行计数更困难。 (C)2016 Elsevier B.V.保留所有权利。

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