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- W3204887334 abstract "Quantified conflict-driven clause learning (QCDCL) is one of the main approaches for solving quantified Boolean formulas (QBF). We formalise and investigate several versions of QCDCL that include cube learning and/or pure-literal elimination, and formally compare the resulting solving models via proof complexity techniques. Our results show that almost all of the QCDCL models are exponentially incomparable with respect to proof size (and hence solver running time), pointing towards different orthogonal ways how to practically implement QCDCL." @default.
- W3204887334 created "2021-10-11" @default.
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- W3204887334 date "2022-07-01" @default.
- W3204887334 modified "2023-10-14" @default.
- W3204887334 title "QCDCL with Cube Learning or Pure Literal Elimination - What is Best?" @default.
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- W3204887334 doi "https://doi.org/10.24963/ijcai.2022/245" @default.
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