Adaptive Saturation-Based Reasoning

  • Alexandre Riazanov
  • Andrei Voronkov
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2244)

Abstract

For most applications of first-order theorem provers a proof should be found within a fixed time limit. When the time limit is set, systems can perform much better by using algorithms other than the ordinary complete ones. In this paper we describe the Limited Resource Strategy intended to improve performance of resolution- and paramodulation- based provers when a fixed limit is imposed on the time of a run. We give experimental evidence that the Limited Resource Strategy gives a significant improvement over the OTTER saturation algorithm, algorithms not using passive clauses for simplification and the weightbased algorithms.

Keywords

Theorem Prover Priority Queue Automate Reasoning Weight Limit Benchmark Suite 
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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References

  1. 1.
    J. Avenhaus, J. Denzinger, and M. Fuchs. DISCOUNT: a system for distributed equational deduction. In J. Hsiang, editor, Proceedings of the 6th International Conference on Rewriting Techniques and Applications (RTA—95), volume 914 of Lecture Notes in Computer Science, pages 397–402, Kaiserslautern, 1995.Google Scholar
  2. 2.
    H. de Nivelle. Bliksem 1.10 User’s Manual. MPI für Informatik, Saarbrücken, 2000.Google Scholar
  3. 3.
    P. Graf. Term Indexing, volume 1053 of Lecture Notes in Computer Science. Springer Verlag, 1996.Google Scholar
  4. 4.
    Th. Hillenbrand, A. Buch, R. Vogt, and B. Löchner. Waldmeister: Highperformance equational deduction. Journal of Automated Reasoning, 18(2):265–270, 1997.CrossRefGoogle Scholar
  5. 5.
    E.L. Lusk. Controlling redundancy in large search spaces: Argonne-style theorem proving through the years. In A. Voronkov, editor, Logic Programming and Automated Reasoning. International Conference LPAR’92., volume 624 of Lecture Notes in Artificial Intelligence, pages 96–106, St.Petersburg, Russia, July 1992.Google Scholar
  6. 6.
    W.W. McCune. OTTER 3.0 reference manual and guide. Technical Report ANL-94/6, Argonne National Laboratory, January 1994.Google Scholar
  7. 7.
    M. Moser, O. Ibens, R. Letz, J. Steinbach, C. Goller, J. Schumann, and K. Mayr. SETHEO and E-SETHEO-the CADE-13 systems. Journal of Automated Reasoning, 18:237–246, 1997.CrossRefGoogle Scholar
  8. 8.
    I.V. Ramakrishnan, R. Sekar, and A. Voronkov. Term indexing. In A. Robinson and A. Voronkov, editors, Handbook of Automated Reasoning, volume II, chapter 26, pages 1853–1964. Elsevier Science, 2001.Google Scholar
  9. 9.
    A. Riazanov and A. Voronkov. Vampire. In H. Ganzinger, editor, Automated Deduction-CADE-16. 16th International Conference on Automated Deduction, volume 1632 of Lecture Notes in Artificial Intelligence, pages 292–296, Trento, Italy, July 1999.Google Scholar
  10. 10.
    A. Riazanov and A. Voronkov. Vampire 1.1 (system description). In R. Gore, A. Leitsch, and T. Nipkow, editors, Automated Reasoning. First International Joint Conference, IJCAR 2001, volume 2083 of Lecture Notes in Artificial Intelligence, pages 376–380, Siena, Italy, June 2001.Google Scholar
  11. 11.
    S. Schulz. System abstract: E 0.61. In R. Gore, A. Leitsch, and T. Nipkow, editors, Automated Reasoning. First International Joint Conference, IJCAR 2001, volume 2083 of Lecture Notes in Artificial Intelligence, pages 370–375, Siena, Italy, June 2001.Google Scholar
  12. 12.
    J. Schumann and B. Fischer. NORA/HAMMR: Making deduction-based software component retrieval practical. In Proc. Automated Software Engineering (ASE-97), pages 246–254, Lake Tahoe, November 1997. IEEE Computer Society Press.Google Scholar
  13. 13.
    G. Sutcliffe. The CADE-16 ATP system competition. Journal of Automated Reasoning, 2000. to appear.Google Scholar
  14. 14.
    T. Tammet. Gandalf. Journal of Automated Reasoning, 18(2):199–204, 1997.CrossRefGoogle Scholar
  15. 15.
    A. Voronkov. CASC 16 1 2. Preprint CSPP-4, Department of Computer Science, University of Manchester, February 2000.Google Scholar
  16. 16.
    C. Weidenbach, B. Afshordel, U. Brahm, C. Cohrs, T. Engel, E. Keen, C. Theobalt, and D. Topic. System description: Spass version 1.0.0. In H. Ganzinger, editor, Automated Deduction—CADE-16. 16th International Conference on Automated Deduction, volume 1632 of Lecture Notes in Artificial Intelligence, pages 378–382,Trento, Italy, July 1999.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Alexandre Riazanov
    • 1
  • Andrei Voronkov
    • 1
  1. 1.University of ManchesterUSA

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