32 research outputs found
QBF Proof Complexity
Quantified Boolean Formulas (QBF) and their proof complexity are not as well understood as
propositional formulas, yet remain an area of interest due to their relation to QBF solving. Proof
systems for QBF provide a theoretical underpinning for the performance of these solvers. We define
a novel calculus IR-calc, which enables unification of the principal existing resolution-based QBF
calculi and applies to the more powerful Dependency QBF (DQBF).
We completely reveal the relative power of important QBF resolution systems, settling in
particular the relationship between the two different types of resolution-based QBF calculi. The
most challenging part of this comparison is to exhibit hard formulas that underlie the exponential
separations of the proof systems. In contrast to classical proof complexity we are currently short
of lower bound techniques for QBF proof systems. To this end we exhibit a new proof technique
for showing lower bounds in QBF proof systems based on strategy extraction. We also find that
the classical lower bound techniques of the prover-delayer game and feasible interpolation can be
lifted to a QBF setting and provide new lower bounds.
We investigate more powerful proof systems such as extended resolution and Frege systems. We
define and investigate new QBF proof systems that mix propositional rules with a reduction rule,
we find the strategy extraction technique also works and directly lifts lower bounds from circuit
complexity. Such a direct transfer from circuit to proof complexity lower bounds has often been
postulated, but had not been formally established for propositional proof systems prior to this work.
This leads to strong lower bounds for restricted versions of QBF Frege, in particular an exponential
lower bound for QBF Frege systems operating with AC0[p] circuits. In contrast, any non-trivial
lower bound for propositional AC0[p]-Frege constitutes a major open problem
Reasons for Hardness in QBF Proof Complexity
Quantified Boolean Formulas (QBF) extend the canonical NP-complete satisfiability problem by including Boolean quantifiers. Determining the truth of a QBF is PSPACE-complete; this is expected to be a harder problem than satisfiability, and hence QBF solving has much wider
applications in practice. QBF proof complexity forms the theoretical basis for understanding QBF solving, as well as providing insights into more general complexity theory, but is less well understood than propositional proof complexity.
We begin this thesis by looking at the reasons underlying QBF hardness, and in particular when the hardness is propositional in nature, rather than arising due to the quantifiers. We introduce relaxing QU-Res, a previous model for identifying such propositional hardness, and construct an example where relaxing QU-Res is unsuccessful in this regard. We then provide a new model for identifying such hardness which we prove captures this concept.
Now equipped with a means of identifying ‘genuine’ QBF hardness, we prove a new lower bound technique for tree-like QBF proof systems. Lower bounds using this technique allows us to show a new separation between tree-like and dag-like systems. We give a characterisation of lower bounds for a large class of tree-like proof systems, in which such lower bounds play a prominent role.
Further to the tree-like bound, we provide a new lower bound technique for QBF proof systems in general. This technique has some similarities to the above technique for tree-like systems, but requires some refinement to provide bounds for dag-like systems. We give applications of this
new technique by proving lower bounds across several systems. The first such lower bounds are for a very simple family of QBFs. We then provide a construction to combine false QBFs to give formulas for which we can show lower bounds in this way, allowing the generation of the first random QBF proof complexity lower bounds
Evaluating QBF Solvers: Quantifier Alternations Matter
We present an experimental study of the effects of quantifier alternations on
the evaluation of quantified Boolean formula (QBF) solvers. The number of
quantifier alternations in a QBF in prenex conjunctive normal form (PCNF) is
directly related to the theoretical hardness of the respective QBF
satisfiability problem in the polynomial hierarchy. We show empirically that
the performance of solvers based on different solving paradigms substantially
varies depending on the numbers of alternations in PCNFs. In related
theoretical work, quantifier alternations have become the focus of
understanding the strengths and weaknesses of various QBF proof systems
implemented in solvers. Our results motivate the development of methods to
evaluate orthogonal solving paradigms by taking quantifier alternations into
account. This is necessary to showcase the broad range of existing QBF solving
paradigms for practical QBF applications. Moreover, we highlight the potential
of combining different approaches and QBF proof systems in solvers.Comment: preprint of a paper to be published at CP 2018, LNCS, Springer,
including appendi
Proof Complexity for Quantified Boolean Formulas
Quantified Boolean formulas (QBF) extend the propositional satisfiability problem by allowing variables to be universally as well as existentially quantified. Deciding whether a QBF is true or false is PSPACE-complete and a wide range of mathematical and industrial problems can be expressed as QBFs. QBF proof complexity is the theoretical analysis of algorithmic techniques for solving QBFs.
We make a detailed comparison of the proof systems Q-Res, QU-Res, and ∀Exp + Res which extend propositional Resolution with different rules for reasoning about universally quantified variables. We give new simulation and separation results between these proof systems under two natural restrictions, when the proofs are tree-like, and when the QBFs have bounded quantifier complexity.
We consider a strong QBF proof system, QRAT, proposed as a universal proof checking format. We show that, unless P = PSPACE, QRAT does not admit strategy extraction. This is proved by constructing a family of QBFs that have short QRAT proofs but whose strategies are hard to compute in general. We also explore why strategy extraction fails for QRAT, including presenting a restricted version of QRAT which does admit strategy extraction.
We study two results from propositional proof complexity and their analogues in QBF proof complexity, showing in both cases how the additional complexity of QBF solving compared to refuting propositional formulas causes these results to fail in the QBF setting
Lower Bound Techniques for QBF Proof Systems
How do we prove that a false QBF is inded false? How big a proof is needed? The special case when all quantifiers are existential is the well-studied setting of propositional proof complexity. Expectedly, universal quantifiers change the game significantly. Several proof systems have been designed in the last couple of decades to handle QBFs. Lower bound paradigms from propositional proof complexity cannot always be extended - in most cases feasible interpolation and consequent transfer of circuit lower bounds works, but obtaining lower bounds on size by providing lower bounds on width fails dramatically. A new paradigm with no analogue in the propositional world has emerged in the form of strategy extraction, allowing for transfer of circuit lower bounds, as well as obtaining independent
genuine QBF lower bounds based on a semantic cost measure.
This talk will provide a broad overview of some of these developments
Towards Uniform Certification in QBF
We pioneer a new technique that allows us to prove a multitude of previously open simulations in QBF proof complexity. In particular, we show that extended QBF Frege p-simulates clausal proof systems such as IR-Calculus, IRM-Calculus, Long-Distance Q-Resolution, and Merge Resolution. These results are obtained by taking a technique of Beyersdorff et al. (JACM 2020) that turns strategy extraction into simulation and combining it with new local strategy extraction arguments.
This approach leads to simulations that are carried out mainly in propositional logic, with minimal use of the QBF rules. Our proofs therefore provide a new, largely propositional interpretation of the simulated systems. We argue that these results strengthen the case for uniform certification in QBF solving, since many QBF proof systems now fall into place underneath extended QBF Frege
Hard QBFs for Merge Resolution
We prove the first proof size lower bounds for the proof system Merge Resolution (MRes [Olaf Beyersdorff et al., 2020]), a refutational proof system for prenex quantified Boolean formulas (QBF) with a CNF matrix. Unlike most QBF resolution systems in the literature, proofs in MRes consist of resolution steps together with information on countermodels, which are syntactically stored in the proofs as merge maps. As demonstrated in [Olaf Beyersdorff et al., 2020], this makes MRes quite powerful: it has strategy extraction by design and allows short proofs for formulas which are hard for classical QBF resolution systems.
Here we show the first exponential lower bounds for MRes, thereby uncovering limitations of MRes. Technically, the results are either transferred from bounds from circuit complexity (for restricted versions of MRes) or directly obtained by combinatorial arguments (for full MRes). Our results imply that the MRes approach is largely orthogonal to other QBF resolution models such as the QCDCL resolution systems QRes and QURes and the expansion systems ?Exp+Res and IR
Genuine Lower Bounds for QBF Expansion
We propose the first general technique for proving genuine lower bounds in expansion-based QBF proof systems. We present the technique in a framework centred on natural properties of winning strategies in the 'evaluation game' interpretation of QBF semantics. As applications, we prove an exponential proof-size lower bound for a whole class of formula families, and demonstrate the power of our approach over existing methods by providing alternative short proofs of two known hardness results. We also use our technique to deduce a result with manifest practical import: in the absence of propositional hardness, formulas separating the two major QBF expansion systems must have unbounded quantifier alternations