منابع مشابه
Dependency Learning for QBF
Quantified Boolean Formulas (QBFs) can be used to succinctly encode problems from domains such as formal verification, planning, and synthesis. One of the main approaches to QBF solving is Quantified Conflict Driven Clause Learning (QCDCL). By default, QCDCL assigns variables in the order of their appearance in the quantifier prefix so as to account for dependencies among variables. Dependency ...
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 کاملDepQBF: A Dependency-Aware QBF Solver
We present DepQBF 0.1, a new search-based solver for quantified boolean formulae (QBF). It integrates compact dependency graphs to overcome the restrictions imposed by linear quantifier prefixes of QBFs in prenex conjunctive normal form (PCNF). DepQBF 0.1 was placed first in the main track of QBFEVAL’10 in a score-based ranking. We provide a general system overview and describe selected orthogo...
متن کاملEfficiently Representing Existential Dependency Sets for Expansion-based QBF Solvers
Given a quantified boolean formula (QBF) in prenex conjunctive normal form (PCNF), we consider the problem of identifying variable dependencies. In related work, a formal definition of dependencies has been suggested based on quantifier prefix reordering: two variables are independent if swapping them in the prefix does not change satisfiability of the formula. Instead of the general case, we f...
متن کاملSmall Resolution Proofs for QBF using Dependency Treewidth
In spite of the close connection between the evaluation of quantified Boolean formulas (QBF) and propositional satisfiability (SAT), tools and techniques which exploit structural properties of SAT instances are known to fail for QBF. This is especially true for the structural parameter treewidth, which has allowed the design of successful algorithms for SAT but cannot be straightforwardly appli...
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ژورنال
عنوان ژورنال: Journal of Artificial Intelligence Research
سال: 2019
ISSN: 1076-9757
DOI: 10.1613/jair.1.11529