Dynamically Partitioning for Solving QBF
نویسندگان
چکیده
In this paper we present a new technique to solve Quantified Boolean Formulas (QBF). Our technique applies the idea of dynamic partitioning to QBF solvers. Dynamic partitioning has previously been utilized in #SAT solvers that count the number of models of a propositional formula. One of the main differences with the #SAT case comes from the solution learning techniques employed in search based QBF solvers. Extending solution learning to a partitioning solver involves some considerable complexities which we show how to resolve. We have implemented our ideas in a new QBF solver, and demonstrate that dynamic partitioning is able to increase the performance of search based solvers, sometimes significantly. Empirically our new solver offers performance that is superior to other search based solvers and in many cases superior to non-search based solvers.
منابع مشابه
Solving Quantified Boolean Formulas
Solving Quantified Boolean Formulas Horst Samulowitz Doctor of Philosophy Graduate Department of Computer Science University of Toronto 2007 Many real-world problems do not have a simple algorithmic solution and casting these problems as search problems is often not only the simplest way of casting them, but also the most efficient way of solving them. In this thesis we will present several tec...
متن کاملEnhancing Search-Based QBF Solving by Dynamic Blocked Clause Elimination
Among preprocessing techniques for quantified Boolean formula (QBF) solving, quantified blocked clause elimination (QBCE) has been found to be extremely effective. We investigate the power of dynamically applying QBCE in search-based QBF solving with clause and cube learning (QCDCL). This dynamic application of QBCE is in sharp contrast to its typical use as a mere preprocessing technique. In o...
متن کاملLearning to Solve QBF
We present a novel approach to solving Quantified Boolean Formulas (QBF) that combines a search-based QBF solver with machine learning techniques. We show how classification methods can be used to predict run-times and to choose optimal heuristics both within a portfolio-based, and within a dynamic, online approach. In the dynamic method variables are set to a truth value according to a scheme ...
متن کاملA Symbolic Search Based Approach for Quantified Boolean Formulas
Solving Quantified Boolean Formulas (QBF) has become an important and attractive research area, since several problem classes might be formulated efficiently as QBF instances (e.g. planning, non monotonic reasoning, twoplayer games, model checking, etc). Many QBF solvers has been proposed, most of them perform decision tree search using the DPLL-like techniques. To set free the variable orderin...
متن کاملShortening QBF Proofs with Dependency Schemes
We provide the first proof complexity results for QBF dependency calculi. By showing that the reflexive resolution path dependency scheme admits exponentially shorter Q-resolution proofs on a known family of instances, we answer a question first posed by Slivovsky and Szeider in 2014 [30]. Further, we conceive a method of QBF solving in which dependency recomputation is utilised as a form of in...
متن کامل