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Optimizing a BDD-Based Modal Solver

机译:优化基于BDD的模态求解器

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In an earlier work we showed how a competitive satisfiability solver for the modal logic K can be built on top of a BDD package. In this work we study optimization issues for such solvers. We focus on two types of optimizations. First we study variable ordering, which is known to be of critical importance to BDD-based algorithms. Second, we study modal extensions of the pure-literal rule. Our results show that the payoff of the variable-ordering optimization is rather modest, while the payoff of the pure-literal optimization is quite significant. We benchmark our optimized solver against both native solvers (DLP) and translation-based solvers (MSPASS and SEMPROP). Our results indicate that the BDD-based approach dominates for modally heavy formulas, while search-based approaches dominate for propositionally-heavy formulas.
机译:在较早的工作中,我们展示了如何在BDD包的顶部构建用于模态逻辑K的竞争性可满足性求解器。在这项工作中,我们研究此类求解器的优化问题。我们专注于两种类型的优化。首先,我们研究变量排序,这对于基于BDD的算法至关重要。其次,我们研究纯文字规则的模态扩展。我们的结果表明,变量排序优化的收益是相当适度的,而纯文字优化的收益却是相当可观的。我们将优化的求解器与本机求解器(DLP)和基于翻译的求解器(MSPASS和SEMPROP)进行基准测试。我们的结果表明,基于BDD的方法在模态较重的公式中占主导地位,而基于搜索的方法在命题繁重的公式中占主导地位。

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