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On sufficient conditions for unsatisfiability of random formulas

机译:在充分条件下不满足随机公式

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摘要

A descriptive complexity approach to random 3-SAT is initiated. We show that unsatisfiability of any significant fraction of random 3-CNF formulas cannot be certified by any property that is expressible in Datalog. Combined with the known relationship between the complexity of constraint satisfaction problems and expressibility in Datalog, our result implies that any constraint propagation algorithm working with small constraints will fail to certify unsatisfiability almost always. Our result is a consequence of designing a winning strategy for one of the players in the existential pebble game. The winning strategy makes use of certain extension axioms that we introduce and hold almost surely on a random 3-CNF formula. The second contribution of our work is the connection between finite model theory and propositional proof complexity. To make this connection explicit, we establish a tight relationship between the number of pebbles needed to win the game and the width of the Resolution refutations. As a consequence to our result and the known size--width relationship in Resolution, we obtain new proofs of the exponential lower bounds for Resolution refutations of random 3-CNF formulas and the Pigeonhole Principle.
机译:提出了一种描述性复杂度方法,用于随机3-SAT。我们表明,随机3-CNF公式的任何显着部分的不满足性都无法通过Datalog中可表示的任何属性来证明。结合约束满足问题的复杂性和Datalog的可表达性之间的已知关系,我们的结果表明,任何处理小的约束的约束传播算法都几乎无法始终证明不满足。我们的结果是为存在的卵石游戏中的一名玩家设计了一个获胜策略的结果。获胜策略利用了我们引入的某些扩展公理,并且几乎肯定地将其保留在随机的3-CNF公式中。我们工作的第二个贡献是有限模型理论与命题证明复杂性之间的联系。为了使这种联系清晰明了,我们在赢得比赛所需的卵石数量与“分辨率”引用的宽度之间建立了紧密的关系。作为我们结果的结果以及``分辨率''中已知的大小宽度关系,我们获得了关于随机3-CNF公式的分辨率反驳和Pigeonhole原理的指数下界的新证明。

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