Many real-world problems are encoded into SAT instances and efficiently solved by CDCL (Conflict-Driven Clause Learning) SAT solvers. However, some scenarios require distributed problem solving approaches. Privacy is often the main reason. This motivates the need to solve distributed SAT problems We analyze how this problem can be tacked in an efficient way, and present ABTSAT, a new version of the ABT (Asynchronous Backtracking) algorithm adapted to solve distributed SAT instances. It combines ABT execution with calls to CDCL SAT solvers and clause learning. ABTSAT is sound and complete, properties inherited from ABT, and solves local problems efficiently by using CDCL SAT solvers.
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机译：许多真实世界问题被编码到SAT实例中，并通过CDCL（冲突驱动的条款学习）饱和宿主有效解决。但是，某些情况需要分布式问题解决方法。隐私通常是主要原因。这激励了解决分布式SAT问题的需求，我们分析了如何以有效的方式加上这个问题，并且目前的Abtsat，ABT（异步回溯）算法的新版本适于解决分布式SAT实例。它将ABT执行与CDCL SAT SOLVERS和CHERAUND学习的调用相结合。 Abtsat是良好的，从ABT继承的属性，通过使用CDCL SAT求解器有效地解决了当地问题。
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