Skip to main content

Automata and Answer Set Programming

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5407))

Abstract

In answer set programming (ASP), one does not allow the use of function symbols. Disallowing function symbols avoids the problem of having logic programs which have stable models of excessively high complexity. For example, Marek, Nerode, and Remmel showed that there exist finite predicate logic programs which have stable models but which have no hyperarithmetic stable model. Of course, by eliminating function symbols, one loses a lot of expressive power in the language. In particular, it is difficult to directly reason about infinite sets in ASP.

Blair, Marek, and Remmel [BMR08] developed an extension of logic programming called set based logic programming. In the theory of set based logic programming, the atoms represent subsets of a fixed universe X and one is allowed to compose the one-step consequence operator with a monotonic idempotent operator O so as to ensure that the analogue of stable models are always closed under O. We show that if the sets represented by the atoms in a finite set based program P are languages accepted by finite automaton, and the operators involved in the construction have a certain natural property, then all the stable models of P are languages accepted by finite automaton and one can effectively check whether a language accepted by a finite automaton is a stable model of the set based logic program. Thus in this setting, one can effectively reason about certain classes of infinite sets.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Apt, K., Blair, H.A.: Arithmetic Classification of Perfect Models of Stratified Programs. Fundamenta Informaticae 13, 1–17 (1990)

    MathSciNet  MATH  Google Scholar 

  2. Babovich, Y., Lifschitz, V.: Cmodels (2002), http://www.cs.utexas.edu/users/tag/cmodels.html

  3. Baral, C.: Knowledge Representation, Reasoning and Declarative Problem Solving. Cambridge University Press, Cambridge (2003)

    Book  MATH  Google Scholar 

  4. Blair, H.A., Marek, V.W., Remmel, J.B.: Spatial Logic Programming. In: Proceedings SCI 2001, Orlando, FL (July 2001)

    Google Scholar 

  5. Blair, H.A., Marek, V.W., Remmel, J.B.: Set Based Logic Programming (in print)

    Google Scholar 

  6. Blair, H.A., Marek, V.W., Schlipf, J.S.: The expressivness of locally stratified programs. Annals of Mathematics and Artificial Intelligence 15, 209–229 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  7. Blumensath, A., Grädel, E.: Automatic Structures. In: Proceedings of the 15th Symposium on Logic in Computer Science LICS 2000, pp. 51–62 (2000)

    Google Scholar 

  8. Denecker, M.: Extending classical logic with inductive definitions. In: Palamidessi, C., Moniz Pereira, L., Lloyd, J.W., Dahl, V., Furbach, U., Kerber, M., Lau, K.-K., Sagiv, Y., Stuckey, P.J. (eds.) CL 2000. LNCS, vol. 1861, pp. 703–717. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  9. Dowling, W.F., Gallier, J.H.: Linear-time algorithms for testing satisfiability of propositional Horn formulae. Journal of Logic Programming 3, 267–284 (1984)

    Article  MathSciNet  MATH  Google Scholar 

  10. Gebser, M., Kaufmann, B., Neumann, A., Schaub, T.: Clasp – a Conflict-driven Answer Set Solver. In: Baral, C., Brewka, G., Schlipf, J. (eds.) LPNMR 2007. LNCS, vol. 4483, pp. 260–265. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  11. Gelfond, M.: Logic Programming and Knowledge Representation – A-Prolog perspective. Artificial Intelligence Journal 138, 3–38 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  12. Gelfond, M., Lifschitz, V.: The stable model semantics for logic programming. In: Proceedings of the International Joint Conference and Symposium on Logic Programming, pp. 1070–1080. MIT Press, Cambridge (1988)

    Google Scholar 

  13. Giunchiglia, E., Lierer, Y., Maratea, M.: Answer Set Programming Based on Propositional Satisfiability. Journal of Automated Reasoning 36, 345–377 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  14. Khoussainov, B., Nerode, A.: Automatic Presentations of Structures. In: Leivant, D. (ed.) LCC 1994. LNCS, vol. 960, pp. 367–392. Springer, Heidelberg (1995)

    Chapter  Google Scholar 

  15. Khoussainov, B., Nies, A., Rubin, S., Stephan, F.: Automatic structures: richness and limitations. Logical Methods of Computer Science 3(2), 18 (2007) (electronic)

    Article  MathSciNet  MATH  Google Scholar 

  16. Leone, N., Pfeifer, G., Faber, W., Eiter, T., Gottlob, G., Perri, S., Scarcello, F.: The dlv system for knowledge representation and reasoning. ACM Transactions on Computational Logic (2006)

    Google Scholar 

  17. Lifschitz, V.: Minimal belief and negation as failure. Artificial Intelligence 70, 53–72 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  18. Lin, F., Zhao, Y.: ASSAT: Computing answer sets of a logic program by SAT solvers. In: Proceedings of the 18th National Conference on Artificial Intelligence (AAAI 2002), pp. 112–117. AAAI Press, Menlo Park (2002)

    Google Scholar 

  19. Marek, W., Nerode, A., Remmel, J.B.: The stable models of predicate logic programs. Journal of Logic Programming 21(3), 129–154 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  20. Marek, W., Truszczyński, M.: Nonmonotonic Logic – Context-Dependent Reasoning. Springer, Heidelberg (1993)

    MATH  Google Scholar 

  21. Marek, V.W., Truszczyński, M.: Stable Models and an Alternative Logic Programming Paradigm. In: The Logic Programming Paradigm. Series Artificial Intelligence, pp. 375–398. Springer, Heidelberg (1999)

    Chapter  Google Scholar 

  22. Niemelä, I.: Logic programs with stable model semantics as a constraint programming paradigm. Annals of Mathematics and Artificial Intelligence 25, 3,4, 241–273 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  23. Simons, P., Niemelä, I., Soininen, T.: Extending and implementing stable semantics of logic programs. Artificial Intelligence 138, 181–234 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  24. Smullyan, R.: First-order Logic. Springer, Heidelberg (1968)

    Book  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Marek, V., Remmel, J.B. (2008). Automata and Answer Set Programming. In: Artemov, S., Nerode, A. (eds) Logical Foundations of Computer Science. LFCS 2009. Lecture Notes in Computer Science, vol 5407. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92687-0_22

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-92687-0_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-92686-3

  • Online ISBN: 978-3-540-92687-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics