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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4501))

Abstract

We consider the problem of computing tractable approximations to CNF formulas, extending the approach of Selman and Kautz to compute the Horn-LUB to involve renaming of variables. Negative results are given for the quality of approximation in this extended version. On the other hand, experiments for random 3-CNF show that the new algorithms improve both running time and approximation quality. The output sizes and approximation errors exhibit a ‘Horn bump’ phenomenon: unimodal patterns are observed with maxima in some intermediate range of densities. We also present the results of experiments generating pseudo-random satisfying assignments for Horn formulas.

This material is based upon work supported by the National Science Foundation under grant CCF-0431059. A preliminary version of this work appeared in [14].

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References

  1. Aspvall, B.: Recognizing disguised NR(1) instances of the satisfiability problem. Journal of Algorithms 1, 97–103 (1980)

    Article  MathSciNet  MATH  Google Scholar 

  2. Bollobás, B., Kohayakawa, Y., Łuczak, T.: On the evolution of random Boolean functions. In: Frankl, P., et al. (eds.) Extremal Problems for Finite Sets (Visegrád). Bolyai Society Mathematical Studies, vol. 3, pp. 137–156. János Bolyai Mathematical Society, Budapest (1994)

    Google Scholar 

  3. Boros, E.: Maximum renamable Horn sub-CNFs. Discrete Appl. Math. 96-97, 29–40 (1999)

    Article  MathSciNet  Google Scholar 

  4. Boufkhad, Y.: Algorithms for propositional KB approximation. In: Proceedings of the 15th National Conference on Artificial Intelligence (AAAI-98) and of the 10th Conference on Innovative Applications of Artificial Intelligence (IAAI-98), pp. 280–285 (1998)

    Google Scholar 

  5. Cadoli, M., Donini, F.M.: A survey on knowledge compilation. AI Communications 10(3–4), 137–150 (1997)

    Google Scholar 

  6. Crama, Y., Ekin, O., Hammer, P.L.: Variable and term removal from Boolean formulae. Discrete Applied Mathematics 75(3), 217–230 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  7. Darwiche, A., Marquis, P.: A knowledge compilation map. Journal of Artificial Intelligence Research 17, 229–264 (2002)

    MathSciNet  MATH  Google Scholar 

  8. del Val, A.: First order LUB approximations: characterization and algorithms. Artificial Intelligence 162(1-2), 7–48 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  9. Erdős, P., Rényi, A.: On the evolution of random graphs. Publ. Math. Inst. Hung. Acad. Sci 5, 17–61 (1960)

    Google Scholar 

  10. Horn, A.: On sentences which are true on direct unions of algebras. J. Symbolic Logic 16, 14–21 (1951)

    Article  MathSciNet  MATH  Google Scholar 

  11. Jerrum, M.R., Valiant, L.G., Vazirani, V.V.: Random generation of combinatorial structures from a uniform distribution. Theor. Comput. Sci. 43, 169–188 (1986)

    Article  MathSciNet  MATH  Google Scholar 

  12. Kautz, H., Selman, B.: An empirical evaluation of knowledge compilation by theory approximation. In: Proceedings of the 12th National Conference on Artificial Intelligence, pp. 155–161 (1994)

    Google Scholar 

  13. Kearns, M.J., Vazirani, U.V.: An Introduction to Computational Learning Theory. MIT Press, Cambridge (1994)

    Google Scholar 

  14. Langlois, M., Sloan, R.H., Turán, G.: Horn upper bounds of random 3-CNF: A computational study. In: Ninth Int. Symp. Artificial Intelligence and Mathematics (2006), Available on-line from URL http://anytime.cs.umass.edu/aimath06/

  15. Levin, A.A.: Comparative complexity of disjunctive normal forms (in Russian). Metody Discret. Analiz. 36, 23–38 (1981)

    MATH  Google Scholar 

  16. Lewis, H.R.: Renaming a set of clauses as a Horn set. J. ACM 25, 134–135 (1978)

    MATH  Google Scholar 

  17. McKinsey, J.C.C.: The decision problem for some classes without quantifiers. J. Symbolic Logic 8, 61–76 (1943)

    Article  MathSciNet  MATH  Google Scholar 

  18. Mézard, M., Zecchina, R.: The random K-satisfiability problem: from an analytic solution to an efficient algorithm. Physical Review E 66, 56–126 (2002)

    Article  Google Scholar 

  19. Mora, T., Mézard, M., Zecchina, R.: Pairs of SAT assignments and clustering in random Boolean formulae. Submitted to Theoretical Computer Science (2005), available from URL http://www.citebase.org/cgi-bin/citations?id=oai:arXiv.org:cond-mat/0506053

  20. Roth, D.: On the hardness of approximate reasoning. Artificial Intelligence 82, 273–302 (1996)

    Article  MathSciNet  Google Scholar 

  21. Vardi, M.Y., Aguirre, A.S.M.: Random 3-SAT and BDDs: The Plot Thickens Further. In: Walsh, T. (ed.) CP 2001. LNCS, vol. 2239, pp. 121–136. Springer, Heidelberg (2001)

    Google Scholar 

  22. Selman, B., Kautz, H.: Knowledge compilation and theory approximation. J. ACM 43, 193–224 (1996)

    MathSciNet  MATH  Google Scholar 

  23. Sloan, R.H., Szörényi, B., Turán, G.: On k-term DNF with the maximal number of prime implicants. Submitted for publication. Preliminary version available as Electronic Colloquium on Computational Complexity (ECCC) Technical Report TR05-023, available on-line at http://www.eccc.uni-trier.de/eccc/

  24. Truemper, K.: Effective Logic Computation. Wiley-Interscience, Chichester (1998)

    MATH  Google Scholar 

  25. van Norden, L., van Maaren, H.: Hidden Threshold Phenomena for Fixed-Density SAT-formulae. In: Giunchiglia, E., Tacchella, A. (eds.) SAT 2003. LNCS, vol. 2919, pp. 135–149. Springer, Heidelberg (2004)

    Google Scholar 

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João Marques-Silva Karem A. Sakallah

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Langlois, M., Sloan, R.H., Turán, G. (2007). Horn Upper Bounds and Renaming. In: Marques-Silva, J., Sakallah, K.A. (eds) Theory and Applications of Satisfiability Testing – SAT 2007. SAT 2007. Lecture Notes in Computer Science, vol 4501. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72788-0_11

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  • DOI: https://doi.org/10.1007/978-3-540-72788-0_11

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