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SAT and SMT Are Still Resolution: Questions and Challenges

机译:SAT和SMT仍是解决方案:问题与挑战

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The aim of this invited talk is to discuss strengths, limitations and challenges around one of the simplest yet most powerful practical automated deduction formalisms, namely propositional SAT and its extensions. We will see some of the reasons why CDCL SAT solvers are so effective for finding solutions to so diverse real-world problems, using a single fully automatic push-button strategy, and, by extending them to SAT Modulo Theories (SMT), also to optimization problems and problems with complex (e.g., arithmetic) constraints for which a full encoding into SAT would be too large and/or inefficient. We will give some examples of trade-offs regarding full SAT encodings vs SMT theory solvers, and discuss why SAT and even SMT are just binary resolution strategies, the consequences of this fact, and possible ways to overcome it. Many aspects of the discussion carry over to first-order logic and beyond.
机译:这次受邀演讲的目的是围绕最简单但功能最强大的实用自动演绎形式主义,即命题SAT及其扩展,讨论优势,局限和挑战。我们将看到使用CDCL SAT求解器如此有效的原因,它使用单个全自动按钮策略,并通过将其扩展到SAT模理论(SMT),可以如此有效地找到各种现实问题的解决方案。优化问题和具有复杂(例如算术)约束的问题,对于这些问题,完全编码为SAT会太大和/或效率低下。我们将给出一些有关完整SAT编码与SMT理论求解器的权衡的示例,并讨论为什么SAT甚至SMT只是二进制分辨率策略,这一事实的后果以及克服它的可能方法。讨论的许多方面都涉及一阶逻辑及其他。

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