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Improved Separations of Regular Resolution from Clause Learning Proof Systems

机译:从子句学习证明系统改进常规解析的分离

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摘要

This paper studies the relationship between resolution and conflict driven clause learning (CDCL) without restarts, and refutes some conjectured possible separations. We prove that the guarded, xor-ified pebbling tautology clauses, which Urquhart proved are hard for regular resolution, as well as the guarded graph tautology clauses of Alekhnovich, Johannsen, Pitassi, and Urquhart have polynomial size pool resolution refutations that use only input lemmas as learned clauses. For the latter set of clauses, we extend this to prove that a CDCL search without restarts can refute these clauses in polynomial time, provided it makes the right choices for decision literals and clause learning. This holds even if the CDCL search is required to greedily process conflicts arising from unit propagation. This refutes the conjecture that the guarded graph tautology clauses or the guarded xor-ified pebbling tautology clauses can be used to separate CDCL without restarts from general resolution. Together with subsequent results by Buss and Kolodziejczyk, this means we lack any good conjectures about how to establish the exact logical strength of conflict-driven clause learning without restarts.
机译:本文研究了不重新启动就解决与冲突驱动子句学习(CDCL)之间的关系,并驳斥了一些推测可能的分离。我们证明了Urquhart证明的守卫,xor化的令人讨厌的重言式子句很难进行常规解析,以及Alekhnovich,Johannsen,Pitassi和Urquhart的守卫图重言式子句具有多项式大小池分辨率反驳,仅使用输入引理作为学习条款。对于后一组子句,我们将其扩展为证明无需重新启动的CDCL搜索可以在多项式时间内反驳这些子句,只要它为决策文字和子句学习提供了正确的选择。即使需要CDCL搜索来贪婪地处理由单元传播引起的冲突,这一点仍然成立。这驳斥了这样的推测,即可以使用保护图重言式子句或受保护的异或修饰的重言语子句来分隔CDCL,而无需从通用解析重新启动。加上Buss和Kolodziejczyk随后的研究结果,这意味着我们对如何建立无需重新启动的冲突驱动子句学习的确切逻辑强度缺乏任何好的推测。

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