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Model Representation over Finite and Infinite Signatures

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Logics in Artificial Intelligence (JELIA 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4160))

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Abstract

Computationally adequate representation of models is a topic arising in various forms in logic and AI. Two fundamental decision problems in this area are: (1) to check whether a given clause is true in a represented model, and (2) to decide whether two representations of the same type represent the same model. ARMs, contexts and DIGs are three important examples of model representation formalisms. The complexity of the mentioned decision problems has been studied for ARMs only for finite signatures, and for contexts and DIGs only for infinite signatures, so far. We settle the remaining cases. Moreover we show that, similarly to the case for infinite signatures, contexts and DIGs allow one to represent the same classes of models also over finite signatures; however DIGs may be exponentially more succinct than all equivalent contexts.

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References

  1. Baumgartner, P., Tinelli, C.: The model evolution calculus. In: Baader, F. (ed.) CADE 2003. LNCS, vol. 2741, pp. 350–364. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  2. Baumgartner, P., Tinelli, C.: The model evolution calculus with equality. In: Nieuwenhuis, R. (ed.) CADE 2005. LNCS, vol. 3632, pp. 392–408. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  3. Baumgartner, P., Fuchs, A., Tinelli, C.: Lemma Learning in the Model Evolution Calculus (submitted)

    Google Scholar 

  4. Comon, H., Delor, C.: Equational formulae with membership constraints. Information and Computation 112(2), 167–216 (1994)

    Article  MATH  MathSciNet  Google Scholar 

  5. Caferra, R., Zabel, N.: Extending resolution for model construction. In: van Eijck, J. (ed.) JELIA 1990. LNCS (LNAI), vol. 478, pp. 153–169. Springer, Heidelberg (1991)

    Chapter  Google Scholar 

  6. Caferra, R., Leitsch, A., Peltier, N.: Automated Model Building. Applied Logic Series, vol. 31. Kluwer Academic Publishers, Dordrecht (2004)

    MATH  Google Scholar 

  7. Eiter, T., Faber, W., Traxler, P.: Testing strong equivalence of datalog programs - implementation and examples. In: Baral, C., Greco, G., Leone, N., Terracina, G. (eds.) LPNMR 2005. LNCS, vol. 3662, pp. 437–441. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  8. Eiter, T., Fink, M., Tompits, H., Traxler, P., Woltran, S.: Replacements in non-ground answer set programming. In: Proc. of WLP 2006, pp. 145–153 (2006)

    Google Scholar 

  9. Fermüller, C.G., Leitsch, A.: Model building by resolution. In: Martini, S., Börger, E., Kleine Büning, H., Jäger, G., Richter, M.M. (eds.) CSL 1992. LNCS, vol. 702, pp. 134–148. Springer, Heidelberg (1993)

    Google Scholar 

  10. Fermüller, C.G., Leitsch, A.: Hyperresolution and automated model building. Journal of Logic and Computation 6(2), 173–203 (1996)

    Article  MATH  MathSciNet  Google Scholar 

  11. Fermüller, C., Pichler, R.: Model representation via contexts and implicit generalizations. In: Nieuwenhuis, R. (ed.) CADE 2005. LNCS, vol. 3632, pp. 409–423. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  12. Gottlob, G., Pichler, R.: Working with ARMs: Complexity results on atomic representations of Herbrand models. Information and Computation 165, 183–207 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  13. Kapur, D., Narendran, P., Rosenkrantz, D., Zhang, H.: Sufficient-completeness, ground-reducibility and their complexity. Acta Informatica 28(4), 311–350 (1991)

    Article  MATH  MathSciNet  Google Scholar 

  14. Kunen, K.: Answer sets and negation as failure. In: Proceedings of ICLP 1987, pp. 219–228. MIT Press, Cambridge (1987)

    Google Scholar 

  15. Lassez, J.-L., Marriott, K.: Explicit representation of terms defined by counter examples. Journal of Automated Reasoning 3(3), 301–317 (1987)

    Article  MATH  MathSciNet  Google Scholar 

  16. Martelli, A., Montanari, U.: An efficient unification algorithm. ACM Transactions on Programming Languages and Systems 4(2), 258–282 (1982)

    Article  MATH  Google Scholar 

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Fermüller, C.G., Pichler, R. (2006). Model Representation over Finite and Infinite Signatures. In: Fisher, M., van der Hoek, W., Konev, B., Lisitsa, A. (eds) Logics in Artificial Intelligence. JELIA 2006. Lecture Notes in Computer Science(), vol 4160. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11853886_15

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  • DOI: https://doi.org/10.1007/11853886_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-39625-3

  • Online ISBN: 978-3-540-39627-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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