Strong (D)QBF Dependency Schemes via Implication-free Resolution Paths

Author:

Beyersdorff Olaf1ORCID,Blinkhorn Joshua Lewis2ORCID,Peitl Tomáš3ORCID

Affiliation:

1. Friedrich-Schiller-Universität, Jena, Germany

2. Friedrich-Schiller-Universität, Jena Germany

3. Institute of Logic and Computation, Technische Universitat Wien, Vienna Austria

Abstract

We suggest a general framework to study dependency schemes for dependency quantified Boolean formulas (DQBF). As our main contribution, we exhibit a new infinite collection of implication-free DQBF dependency schemes that generalise the reflexive resolution path dependency scheme. We establish soundness of all these schemes, implying that they can be used in any DQBF proof system. We further explore the power of QBF and DQBF resolution systems parameterised by implication-free dependency schemes and show that the hierarchical structure naturally present among the dependency schemes translates isomorphically to a hierarchical structure of parameterised proof systems with respect to p-simulation. As a special case, we demonstrate that our new schemes are exponentially stronger than the reflexive resolution path dependency scheme when used in Q-resolution, thus resulting in the strongest QBF dependency schemes known to date.

Publisher

Association for Computing Machinery (ACM)

Reference44 articles.

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3. Valeriy Balabanov, Magdalena Widl, and Jie-Hong R. Jiang. 2014. QBF Resolution Systems and Their Proof Complexities. In International Conference on Theory and Practice of Satisfiability Testing (SAT)(Lecture Notes in Computer Science, Vol.  8561), Carsten Sinz and Uwe Egly (Eds.). Springer, Vienna, 154–169.

4. Olaf Beyersdorff. 2022. Proof Complexity of Quantified Boolean Logic – a Survey. In Mathematics for Computation (M4C) Marco Benini Olaf Beyersdorff Michael Rathjen and Peter Schuster (Eds.). World Scientific 353–391.

5. Olaf Beyersdorff and Joshua Blinkhorn. 2016. Dependency Schemes in QBF Calculi: Semantics and Soundness. In International Conference on Principles and Practice of Constraint Programming (CP)(Lecture Notes in Computer Science, Vol.  9892), Michel Rueher (Ed.). Springer, Toulouse, 96–112.

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