On Q-Resolution and CDCL QBF Solving

  • Mikoláš JanotaEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9710)


The proof system Q-resolution and its variations provide the underlying proof systems for the DPLL-based QBF solvers. While (long-distance) Q-resolution models a conflict driven clause learning (CDCL) QBF solver, the inverse relation is not well understood. This paper shows that CDCL solving not only does not simulate Q-resolution, but also that this is deeply embedded in the workings of the solver. This contrasts with SAT solving, where CDCL solvers have been shown to simulate resolution.


Conjunctive Normal Form Propositional Formula Unit Clause Universal Variable Resolution Step 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Microsoft ResearchCambridgeUK

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