Abstract
We propose some general techniques for proving lower bounds in expansion-based QBF proof systems. We present them 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 an interesting result: in the absence of propositional hardness, formulas separating the two major QBF expansion systems must have unbounded quantifier alternations.
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Notes
Proof system P1 simulates proof system P2 whenever P1-proofs and be transformed into P2-proofs with at most polynomial increase in proof size.
This is our notation; in [30], the formulas are referred to as ‘(2)’.
That such a clause and its subderivation remain is proved as part of Proposition 2. We note that this subderivation may include weakening steps – the addition of arbitrary literals to a clause – but such steps are easily erased from a refutation.
In fact, the authors separated Q-Res from ∀Exp+Res; since IR-calcp-simulates Q-Res [9], the result stated in the text is an immediate corollary.
References
Bacchus, F., Walsh, T. (eds.): International conference on theory and practice of satisfiability testing (SAT), Lecture notes in computer science, vol. 3569. Springer, Berlin (2005)
Balabanov, V., Jiang, J.R., Janota, M., Widl, M.: Efficient extraction of QBF (counter)models from long-distance resolution proofs. In: Conference on artificial intelligence (AAAI), pp. 3694–3701 (2015)
Balabanov, V., Widl, M., Jiang, J.R.: QBF resolution systems and their proof complexities. In: Sinz, C., Egly, U. (eds.) International conference on theory and applications of satisfiability testing (SAT), Lecture notes in computer science, vol. 8561, pp. 154–169. Springer (2014)
Ben-Sasson, E., Wigderson, A.: Short proofs are narrow - resolution made simple. J. ACM 48(2), 149–169 (2001)
Benedetti, M., Mangassarian, H.: QBF-based formal verification: Experience and perspectives. Journal on Satisfiability Boolean Modeling and Computation (JSAT) 5(1–4), 133–191 (2008)
Beyersdorff, O., Blinkhorn, J.: Genuine lower bounds for QBF expansion. In: Niedermeier, R., Vallée, B. (eds.) International symposium on theoretical aspects of computer science (STACS), Leibniz international proceedings in informatics (LIPIcs), vol. 96, pp. 12:1–12:15. Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik (2018)
Beyersdorff, O., Blinkhorn, J., Hinde, L.: Size, cost, and capacity: A semantic technique for hard random qbfs. Logical Methods in Computer Science 15(1) (2019)
Beyersdorff, O., Bonacina, I., Chew, L.: Lower bounds: From circuits to QBF proof systems. In: Sudan, M. (ed.) ACM conference on innovations in theoretical computer science (ITCS), pp. 249–260. ACM (2016)
Beyersdorff, O., Chew, L., Janota, M.: On unification of QBF resolution-based calculi. In: Csuhaj-Varjú, E., Dietzfelbinger, M., Ésik, Z. (eds.) International symposium on mathematical foundations of computer science (MFCS), Lecture notes in computer science, vol. 8635, pp. 81–93. Springer (2014)
Beyersdorff, O., Chew, L., Janota, M.: Proof complexity of resolution-based QBF calculi. In: Mayr, E.W., Ollinger, N. (eds.) International symposium on theoretical aspects of computer science (STACS), Leibniz international proceedings in informatics (LIPIcs), vol. 30, pp. 76–89. Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik (2015)
Beyersdorff, O., Chew, L., Mahajan, M., Shukla, A.: Feasible interpolation for QBF resolution calculi. Logical Methods in Computer Science 13 (2017)
Beyersdorff, O., Chew, L., Mahajan, M., Shukla, A.: Are short proofs narrow? QBF resolution is not so simple. ACM Trans. Comput. Log. 19(1), 1:1–1:26 (2018)
Beyersdorff, O., Chew, L., Sreenivasaiah, K.: A game characterisation of tree-like Q-resolution size. Journal of Computer and System Sciences. In press (2017)
Beyersdorff, O., Galesi, N., Lauria, M.: A characterization of tree-like resolution size. Inf. Process. Lett. 113(18), 666–671 (2013)
Beyersdorff, O., Hinde, L., Pich, J.: Reasons for hardness in QBF proof systems. In: Conference on foundations of software technology and theoretical computer science (FSTTCS) (2017)
Buss, S.R.: Towards NP-P via proof complexity and search. Ann. Pure Appl. Logic 163(7), 906–917 (2012)
Cashmore, M., Fox, M., Giunchiglia, E.: Partially grounded planning as quantified Boolean formula. In: Borrajo, D., Kambhampati, S., Oddi, A., Fratini, S. (eds.) International conference on automated planning and scheduling (ICAPS). AAAI (2013)
Chen, H.: Proof complexity modulo the polynomial hierarchy: Understanding alternation as a source of hardness. ACM Trans. Comput. Theory 9(3), 15:1–15:20 (2017)
Cook, S.A., Nguyen, P.: Logical foundations of proof complexity. Cambridge University Press, Cambridge (2010)
Cook, S.A., Reckhow, R.A.: The relative efficiency of propositional proof systems. J. Symb. Log. 44(1), 36–50 (1979)
Craig, W.: Linear reasoning. A new form of the Herbrand-Gentzen Theorem. J. Symb. Log. 22(3), 250–268 (1957)
Creignou, N., Berre, D.L. (eds.): International conference on theory and practice of satisfiability testing (SAT), Lecture notes in computer science, vol. 9710. Springer, Berlin (2016)
Dershowitz, N., Hanna, Z., Katz, J.: Space-efficient bounded model checking. In: Bacchus and Walsh [1], pp. 502–518
Egly, U.: On stronger calculi for QBFs. In: Creignou and Berre [22], pp. 419–434
Egly, U., Kronegger, M., Lonsing, F., Pfandler, A.: Conformant planning as a case study of incremental QBF solving. Ann. Math. Artif. Intell. 80(1), 21–45 (2017)
Egly, U., Lonsing, F., Widl, M.: Long-distance resolution: Proof generation and strategy extraction in search-based QBF solving. In: International conference on logic for programming, artificial intelligence and reasoning (LPAR), pp. 291–308 (2013)
Giunchiglia, E., Marin, P., Narizzano, M.: Reasoning with quantified Boolean formulas. In: Biere, A., Heule, M., van Maaren, H., Walsh, T. (eds.) Handbook of satisfiability, frontiers in artificial intelligence and applications, vol. 185, pp. 761–780. IOS Press (2009)
Giunchiglia, E., Narizzano, M., Tacchella, A.: QBF reasoning on real-world instances. In: International conference on theory and applications of satisfiability testing (SAT), online proceedings (2004)
Janota, M., Klieber, W., Marques-Silva, J., Clarke, E.M.: Solving QBF with counterexample guided refinement. Artif. Intell. 234, 1–25 (2016)
Janota, M., Marques-Silva, J.: Expansion-based QBF solving versus Q-resolution. Theor. Comput. Sci. 577, 25–42 (2015)
Jordan, C., Kaiser, L.: Experiments with reduction finding. In: Järvisalo, M., Gelder, A.V. (eds.) International conference on theory and applications of satisfiability testing (SAT), Lecture notes in computer science, vol. 7962, pp. 192–207. Springer (2013)
Kleine Büning, H., Karpinski, M., Flögel, A.: Resolution for quantified Boolean formulas. Inf. Comput. 117(1), 12–18 (1995)
Kontchakov, R., Pulina, L., Sattler, U., Schneider, T., Selmer, P., Wolter, F., Zakharyaschev, M.: Minimal module extraction from DL-lite ontologies using QBF solvers. In: Boutilier, C. (ed.) International joint conference on artificial intelligence (IJCAI), pp. 836–841. AAAI Press (2009)
Krajíček, J.: Interpolation theorems, lower bounds for proof systems, and independence results for bounded arithmetic. J. Symb. Log. 62(2), 457–486 (1997)
Krajíček, J.: Bounded arithmetic, propositional logic, and complexity theory encyclopedia of mathematics and its applications, vol. 60. Cambridge University Press, Cambridge (1995)
Ling, A.C., Singh, D.P., Brown, S.D.: FPGA logic synthesis using quantified boolean satisfiability. In: Bacchus and Walsh [1], pp. 444–450
Lonsing, F., Egly, U., Seidl, M.: Q-resolution with generalized axioms. In: Creignou and Berre [22], pp. 435–452
Mangassarian, H., Veneris, A.G., Benedetti, M.: Robust QBF encodings for sequential circuits with applications to verification, debug, and test. IEEE Trans. Comput. 59(7), 981–994 (2010)
Mangassarian, H., Veneris, A.G., Safarpour, S., Benedetti, M., Smith, D.E.: A performance-driven QBF-based iterative logic array representation with applications to verification, debug and test. In: International conference on computer-aided design (ICCAD), pp. 240–245 (2007)
Peitl, T., Slivovsky, F., Szeider, S.: Long distance Q-resolution with dependency schemes. In: Creignou and Berre [22], pp. 500–518
Pudlák, P., Impagliazzo, R.: A lower bound for DLL algorithms for k-SAT (preliminary version). In: Shmoys, D.B. (ed.) Symposium on Discrete Algorithms, pp. 128–136. ACM/SIAM (2000)
Rintanen, J.: Asymptotically optimal encodings of conformant planning in QBF. In: National conference on artificial intelligence (AAAI), pp. 1045–1050. AAAI Press (2007)
Segerlind, N.: The complexity of propositional proofs. Bull. Symb. Log. 13(4), 417–481 (2007)
Staber, S., Bloem, R.: Fault localization and correction with QBF. In: Marques-Silva, J., Sakallah, K.A. (eds.) International conference on theory and applications of satisfiability testing (SAT), Lecture notes in computer science, vol. 4501, pp. 355–368. Springer (2007)
Stockmeyer, L.J., Meyer, A.R.: Word problems requiring exponential time: Preliminary report. In: Aho, A.V., Borodin, A., Constable, R.L., Floyd, R.W., Harrison, M.A., Karp, R.M., Strong, H.R. (eds.) ACM symposium on theory of computing (STOC), pp. 1–9. ACM (1973)
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We thank Meena Mahajan and Anil Shukla for helpful discussions on this work.
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This article is part of the Topical Collection on Special Issue on Theoretical Aspects of Computer Science (2018)
An extended abstract of this article appeared in the proceedings of the conference STACS’18 [6]. Research was supported by grants from the John Templeton Foundation (grant no. 60842), the Carl-Zeiss Foundation, and the EU (Marie Curie IRSES project CORCON).
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Beyersdorff, O., Blinkhorn, J. Lower Bound Techniques for QBF Expansion. Theory Comput Syst 64, 400–421 (2020). https://doi.org/10.1007/s00224-019-09940-0
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DOI: https://doi.org/10.1007/s00224-019-09940-0