Skip to main content

Gearing Up for Effective ASP Planning

  • Chapter

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7265))

Abstract

We elaborate upon incremental modeling techniques for ASP Planning, a term coined by Vladimir Lifschitz at the end of the nineties. Taking up this line of research, we argue that ASP needs both a dedicated modeling methodology and sophisticated solving technology in view of the high practical relevance of dynamic systems in real-world applications.

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. Gelfond, M., Lifschitz, V.: The stable model semantics for logic programming. In: Kowalski, R., Bowen, K. (eds.) Proceedings of the Fifth International Conference and Symposium of Logic Programming (ICLP 1988), pp. 1070–1080. MIT Press (1988)

    Google Scholar 

  2. Lifschitz, V.: Answer set programming and plan generation. Artificial Intelligence 138(1-2), 39–54 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  3. Biere, A., Heule, M., van Maaren, H., Walsh, T. (eds.): Handbook of Satisfiability. Frontiers in Artificial Intelligence and Applications, vol. 185. IOS Press (2009)

    Google Scholar 

  4. Davis, M., Putnam, H.: A computing procedure for quantification theory. Journal of the ACM 7, 201–215 (1960)

    Article  MathSciNet  MATH  Google Scholar 

  5. Davis, M., Logemann, G., Loveland, D.: A machine program for theorem-proving. Communications of the ACM 5, 394–397 (1962)

    Article  MathSciNet  MATH  Google Scholar 

  6. Simons, P., Niemelä, I., Soininen, T.: Extending and implementing the stable model semantics. Artificial Intelligence 138(1-2), 181–234 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  7. Gebser, M., Kaufmann, B., Neumann, A., Schaub, T.: Conflict-driven answer set solving. In: Veloso, M. (ed.) Proceedings of the Twentieth International Joint Conference on Artificial Intelligence (IJCAI 2007), pp. 386–392. AAAI Press/The MIT Press (2007)

    Google Scholar 

  8. Kautz, H., Selman, B.: Planning as satisfiability. In: Neumann, B. (ed.) Proceedings of the Tenth European Conference on Artificial Intelligence (ECAI 1992), pp. 359–363. John Wiley & Sons (1992)

    Google Scholar 

  9. Clarke, E., Biere, A., Raimi, R., Zhu, Y.: Bounded model checking using satisfiability solving. Formal Methods in System Design 19(1), 7–34 (2001)

    Article  MATH  Google Scholar 

  10. Whittemore, J., Kim, J., Sakallah, K.: SATIRE: a new incremental satisfiability engine. In: Proceedings of the Thirty-eighth Conference on Design Automation (DAC 2001), pp. 542–545. ACM Press (2001)

    Google Scholar 

  11. Eén, N., Sörensson, N.: Temporal induction by incremental SAT solving. Electronic Notes in Theoretical Computer Science 89(4) (2003)

    Google Scholar 

  12. Subrahmanian, V., Zaniolo, C.: Relating stable models and AI planning domains. In: Proceedings of the Twelfth International Conference on Logic Programming, pp. 233–247. MIT Press (1995)

    Google Scholar 

  13. Dimopoulos, Y., Nebel, B., Köhler, J.: Encoding Planning Problems in Nonmonotonic Logic Programs. In: Steel, S., Alami, R. (eds.) ECP 1997. LNCS (LNAI), vol. 1348, pp. 169–181. Springer, Heidelberg (1997)

    Chapter  Google Scholar 

  14. Lifschitz, V.: Answer set planning. In: de Schreye, D. (ed.) Proceedings of the International Conference on Logic Programming (ICLP 1999), pp. 23–37. MIT Press (1999)

    Google Scholar 

  15. Rintanen, J.: Planning and SAT. In: [3], ch.15, pp. 483–504

    Google Scholar 

  16. Gebser, M., Kaminski, R., Knecht, M., Schaub, T.: plasp: A prototype for PDDL-based planning in ASP. In: [31], pp. 358–363

    Google Scholar 

  17. Gebser, M., Kaminski, R., Kaufmann, B., Ostrowski, M., Schaub, T., Thiele, S.: Engineering an Incremental ASP Solver. In: Garcia de la Banda, M., Pontelli, E. (eds.) ICLP 2008. LNCS, vol. 5366, pp. 190–205. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

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

    Google Scholar 

  19. Kautz, H., Selman, B.: Pushing the envelope: Planning, propositional logic, and stochastic search. In: Shrobe, H., Senator, T. (eds.) Proceedings of the National Conference on Artificial Intelligence (AAAI), pp. 1194–1201. AAAI Press (1996)

    Google Scholar 

  20. McDermott, D.: PDDL — the planning domain definition language. Technical Report CVC TR-98-003/DCS TR-1165, Yale Center for Computational Vision and Control (1998)

    Google Scholar 

  21. Nau, D., Ghallab, M., Traverso, P.: Automated Planning: Theory and Practice. Morgan Kaufmann Publishers (2004)

    Google Scholar 

  22. Rintanen, J., Heljanko, K., Niemelä, I.: Parallel Encodings of Classical Planning as Satisfiability. In: Alferes, J.J., Leite, J. (eds.) JELIA 2004. LNCS (LNAI), vol. 3229, pp. 307–319. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  23. Kautz, H., McAllester, D., Selman, B.: Encoding plans in propositional logic. In: Aiello, L., Doyle, J., Shapiro, S. (eds.) Proceedings of the Fifth International Conference on Principles of Knowledge Representation and Reasoning (KR 1996), pp. 374–384. Morgan Kaufmann Publishers (1996)

    Google Scholar 

  24. Blum, A., Furst, M.: Fast planning through planning graph analysis. Artificial Intelligence 90(1-2), 279–298 (1997)

    Article  MATH  Google Scholar 

  25. Knecht, M.: Efficient domain-independent planning using declarative programming. M.Sc. thesis, Institute for Informatics, University of Potsdam (2009)

    Google Scholar 

  26. Robinson, N., Gretton, C., Pham, D., Sattar, A.: SAT-based parallel planning using a split representation of actions. In: Gerevini, A., Howe, A., Cesta, A., Refanidis, I. (eds.) Proceedings of the Nineteenth International Conference on Automated Planning and Scheduling (ICAPS 2009), pp. 281–288. AAAI Press (2009)

    Google Scholar 

  27. Gebser, M., Grote, T., Schaub, T.: Coala: A Compiler from Action Languages to ASP. In: Janhunen, T., Niemelä, I. (eds.) JELIA 2010. LNCS, vol. 6341, pp. 360–364. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  28. Gebser, M., Sabuncu, O., Schaub, T.: An incremental answer set programming based system for finite model computation. AI Communications 24(2), 195–212 (2011)

    MathSciNet  MATH  Google Scholar 

  29. Gebser, M., Grote, T., Kaminski, R., Schaub, T.: Reactive answer set programming. In: [31], pp. 54–66

    Google Scholar 

  30. Gebser, M., Grote, T., Kaminski, R., Obermeier, P., Sabuncu, O., Schaub, T.: Stream reasoning with answer set programming: Preliminary report. In: Eiter, T., McIlraith, S. (eds.) Proceedings of the Thirteenth International Conference on Principles of Knowledge Representation and Reasoning (KR 2012). AAAI Press (to appear, 2012)

    Google Scholar 

  31. Delgrande, J.P., Faber, W. (eds.): LPNMR 2011. LNCS (LNAI), vol. 6645. Springer, Heidelberg (2011)

    MATH  Google Scholar 

  32. oclingo, http://www.cs.uni-potsdam.de/oclingo

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Gebser, M., Kaufmann, R., Schaub, T. (2012). Gearing Up for Effective ASP Planning. In: Erdem, E., Lee, J., Lierler, Y., Pearce, D. (eds) Correct Reasoning. Lecture Notes in Computer Science, vol 7265. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30743-0_20

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-30743-0_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-30742-3

  • Online ISBN: 978-3-642-30743-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics