Abstract
An open quantified boolean formula (QBF) is a QBF that contains free (unquantified) variables. A solution to such a QBF is a quantifier-free formula that is logically equivalent to the given QBF. Although most recent QBF research has focused on closed QBF, there are a number of interesting applications that require one to consider formulas with free variables. This article shows how clause/cube learning for DPLL-based closed-QBF solvers can be extended to solve QBFs with free variables. We do this by introducing sequents that generalize clauses and cubes and allow learning facts of the form “under a certain class of assignments, the input formula is logically equivalent to a certain quantifier-free formula”.
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Klieber, W., Janota, M., Marques-Silva, J., Clarke, E. (2013). Solving QBF with Free Variables. In: Schulte, C. (eds) Principles and Practice of Constraint Programming. CP 2013. Lecture Notes in Computer Science, vol 8124. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40627-0_33
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DOI: https://doi.org/10.1007/978-3-642-40627-0_33
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