n this paper we study the problem of yielding robust performances from current state-of-the-art solvers for quantified Boolean formulas (QBFs). Building on top of existing QBF solvers, we implement a new multi-engine solver which can inductively learn its solver selection strategy. Experimental results con- firm that our solver is always more robust than each single engine, that it is stable with respect to various perturbations, and that such results can be partially ex- plained by a handful of features playing a crucial role in our solver.
A Multi-engine Solver for Quantified Boolean Formulas
TACCHELLA, ARMANDO
2007-01-01
Abstract
n this paper we study the problem of yielding robust performances from current state-of-the-art solvers for quantified Boolean formulas (QBFs). Building on top of existing QBF solvers, we implement a new multi-engine solver which can inductively learn its solver selection strategy. Experimental results con- firm that our solver is always more robust than each single engine, that it is stable with respect to various perturbations, and that such results can be partially ex- plained by a handful of features playing a crucial role in our solver.
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