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Complexity of translations from resolution to sequent calculus

Published online by Cambridge University Press:  16 January 2019

GISELLE REIS
Affiliation:
Carnegie Mellon University, Doha, Qatar Email: [email protected], [email protected]
BRUNO WOLTZENLOGEL PALEO
Affiliation:
Carnegie Mellon University, Doha, Qatar Email: [email protected], [email protected]

Abstract

Resolution and sequent calculus are two well-known formal proof systems. Their differences make them suitable for distinct tasks. Resolution and its variants are very efficient for automated reasoning and are in fact the theoretical basis of many theorem provers. However, being intentionally machine oriented, the resolution calculus is not as natural for human beings and the input problem needs to be pre-processed to clause normal form. Sequent calculus, on the other hand, is a modular formalism that is useful for analysing meta-properties of various logics and is, therefore, popular among proof theorists. The input problem does not need to be pre-processed, and proofs are more detailed. However, proofs also tend to be larger and more verbose. When the worlds of proof theory and automated theorem proving meet, translations between resolution and sequent calculus are often necessary. In this paper, we compare three translation methods and analyse their complexity.

Type
Paper
Copyright
© Cambridge University Press 2019 

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References

Baaz, M. and Leitsch, A. (2011). Methods of Cut-Elimination, Trends in Logic, Springer.Google Scholar
Ben-Sasson, E. and Wigderson, A. (2001). Short proofs are narrow – resolution made simple. Journal of ACM 48 (2) 149169.CrossRefGoogle Scholar
Benzmüller, C., Sultana, N., Paulson, L.C. and Theiß, F. (2015). The higher-order prover Leo-II. Journal of Automated Reasoning 55 (4) 389404.CrossRefGoogle ScholarPubMed
Bouton, T., de Oliveira, D.C.B., Déharbe, D. and Fontaine, P. (2009). veriT: An open, trustable and efficient SMT-solver. In: Proceedings of the 22nd International Conference on Automated Deduction, Springer-Verlag, 151–156.CrossRefGoogle Scholar
Chihani, Z., Miller, D. and Renaud, F. (2017). A semantic framework for proof evidence. Journal of Automated Reasoning 59 (3) 287330.CrossRefGoogle Scholar
Cook, S. and Reckhow, R. (1974). On the lengths of proofs in the propositional calculus (preliminary version). In: Proceedings of the 6th Annual ACM Symposium on Theory of Computing, ACM, 135–148.CrossRefGoogle Scholar
Degtyarev, A. and Voronkov, A. (2001). The inverse method. In: Robinson, J. A. and Voronkov, A. (eds.) Handbook of Automated Reasoning, Elsevier and MIT Press, 179272.CrossRefGoogle Scholar
Dunchev, T., Leitsch, A., Libal, T., Weller, D. and Woltzenlogel Paleo, B. (2010). System description: The proof transformation system CERES. In: Giesl, J. and Hähnle, R. (eds.) Automated Reasoning, Springer, Berlin, Heidelberg, 427433.CrossRefGoogle Scholar
Ebner, G., Hetzl, S., Reis, G., Riener, M., Wolfsteiner, S. and Zivota, S. (2016). System description: GAPT 2.0. In: Proceedings of the 8th International Joint Conference on Automated Reasoning, vol. 9706, Springer-Verlag, New York, Inc., New York, NY, USA, 293–301.CrossRefGoogle Scholar
Gentzen, G. (1969). Investigations into logical deductions. In: Szabo, M. E. (ed.) The Collected Papers of Gerhard Gentzen, North-Holland, Amsterdam, 68131.Google Scholar
Hermant, O. (2010). Resolution is cut-free. Journal of Automated Reasoning 44 (3) 245276.CrossRefGoogle Scholar
Hetzl, S., Leitsch, A., Reis, G. and Weller, D. (2014). Algorithmic introduction of quantified cuts. Theoretical Computer Science 549, 116.CrossRefGoogle Scholar
Hetzl, S., Leitsch, A., Weller, D. and Woltzenlogel Paleo, B. (2008). Herbrand sequent extraction. In: Proceedings of the 9th AISC International Conference, 15th Calculemas Symposium, and 7th International MKM Conference on Intelligent Computer Mathematics 462–477.Google Scholar
Hetzl, S., Libal, T., Riener, M. and Rukhaia, M. (2013). Understanding resolution proofs through Herbrand's theorem. In: Proceedings of the Automated Reasoning with Analytic Tableaux and Related Methods: 22nd International Conference, TABLEAUX 2013, Springer, 157–171.Google Scholar
Itegulov, D., Slaney, J. and Woltzenlogel Paleo, B. (2017). Scavenger 0.1: A theorem prover based on conflict resolution. In: de Moura, L. (ed.) Automated Deduction – CADE 26, Springer International Publishing, Cham, 344356.CrossRefGoogle Scholar
Korovin, K. (2008). iProver – An instantiation-based theorem prover for first-order logic (system description). In: Armando, A., Baumgartner, P. and Dowek, G. (eds.) Automated Reasoning, Springer, Berlin, Heidelberg, 292298.CrossRefGoogle Scholar
Kovács, L. and Voronkov, A. (2013). First-order theorem proving and vampire, In: Sharygina, N. and Veith, H. (eds.) Computer Aided Verification, Springer, Berlin, Heidelberg, 135.Google Scholar
Maslov, S.J. (1964). An Inverse Method of Establishing Deducibilities in the Classical Predicate Calculus, Reprinted in Siekmann, Wrightson: Automation of reasoning 1: classical papers on computational logic 1957–1966, 1983, pp. 17–20.Google Scholar
McCune, W. (2005–2010). Prover9 and Mace4. Available at: http://www.cs.unm.edu/mccune/prover9/.Google Scholar
Miller, D. (2013). Foundational proof certificates: Making proof universal and permanent. In: Proceedings of the 8th ACM SIGPLAN International Workshop on Logical Frameworks & Meta-languages: Theory & Practice 1–2.Google Scholar
Miller, D. (2017a). Expansion proofs. In: Woltzenlogel Paleo, B. (ed.) Towards an Encyclopaedia of Proof Systems, 1st edn., College Publications, London, UK, 18.Google Scholar
Miller, D. (2017b). Focused LK. In: Woltzenlogel Paleo, B. (ed.) Towards an Encyclopaedia of Proof Systems, 1st edn., College Publications, London, UK, 7576.Google Scholar
Mints, G. (1990). Gentzen-type systems and resolution rules part I propositional logic, In: Martin-Löf, P. and Mints, G. (eds.) Proceedings of the International Conference on Computer Logic Tallinn, USSR, December 12–16, 1988, Springer, Berlin, Heidelberg, 198–231.Google Scholar
Mints, G. (1993). Gentzen-type systems and resolution rule, part II: Predicate logic, In: Oikkonen, J. and Väänänen, J. (eds.) Proceedings of ASL Summer Meeting, Logic Colloquium, Helsinki, Finland, 15–22 July 1990, Lecture Notes in Logic, vol. 2, Springer-Verlag, 163–190.Google Scholar
Orevkov, V.P. (1982). Lower bounds for increasing complexity of derivations after cut elimination. Journal of Mathematical Sciences 20 (4) 23372350.Google Scholar
Reis, G. (2015). Importing SMT and Connection proofs as expansion trees, In: Proceedings 4th Workshop Proof eXchange for Theorem Proving, 3–10.CrossRefGoogle Scholar
Robinson, J.A. (1965). A machine-oriented logic based on the resolution principle. Journal of the ACM 12 (1) 2341.CrossRefGoogle Scholar
Schulz, S. (2013). System description: E 1.8, In: McMillan, K., Middeldorp, A. and Voronkov, A. (eds.) Proceedings of the 19th Logic for Programming, Artificial Intelligence, and Reasoning, Lecture Notes in Computer Science, vol. 8312, Springer, 735–743.CrossRefGoogle Scholar
Statman, R. (1979). Lower bounds on Herbrand's theorem. In: Proceedings of the American Mathematical Society 104–107.Google Scholar
Urquhart, A. (1995). The complexity of propositional proofs. Bulletin of Symbolic Logic 1 (4) 425467.CrossRefGoogle Scholar
Weidenbach, C., Dimova, D., Fietzke, A., Kumar, R., Suda, M. and Wischnewski, P. (2009). SPASS version 3.5, In: Schmidt, R. A. (ed.) Automated Deduction – CADE-22, Springer, Berlin, Heidelberg, 140145.CrossRefGoogle Scholar
Woltzenlogel Paleo, B. (2008). Herbrand Sequent Extraction, M.Sc. Thesis, VDM-Verlag, Saarbrücken, Germany.Google Scholar
Woltzenlogel Paleo, B. (2010). Atomic cut introduction by resolution: Proof structuring and compression. In: Proceedings of the 16th International Conference on Logic for Programming, Artificial Intelligence, and Reasoning, Revised Selected Papers, 463–480.CrossRefGoogle Scholar