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Comparing Different Prenexing Strategies for Quantified Boolean Formulas

机译:比较量化布尔公式的不同前列策略

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The majority of the currently available solvers for quantified Boolean formulas (QBFs) process input formulas only in prenex conjunctive normal form. However, the natural representation of practicably relevant problems in terms of QBFs usually results in formulas which are not in a specific normal form. Hence, in order to evaluate such QBFs with available solvers, suitable normal-form translations are required. In this paper, we report experimental results comparing different prcnexing strategies on a class of structured benchmark problems. The problems under consideration encode the evaluation of nested counterfactuals over a prepositional knowledge base, and span the entire polynomial hierarchy. The results show that different prenexing strategies influence the evaluation time in different ways across different solvers. In particular, some solvers are robust to the chosen strategies while others are not.
机译:目前可用求解器的大多数用于量化布尔公式(QBFS)的进入公式仅在Prenex联合正常形式中。然而,在QBF方面的可行相关问题的自然表示通常导致不具备特定正常形式的公式。因此,为了评估具有可用溶剂的这种QBFS,需要适当的正常形式翻译。在本文中,我们报告了对一类结构性基准问题的不同危害策略的实验结果。正在考虑的问题对介词知识库进行编码对嵌套反事实的评估,并跨越整个多项式层次结构。结果表明,不同的前列策略在不同求解器上以不同方式影响评价时间。特别是,一些求解器对所选择的策略具有强大而其他求解器。

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