Skip to main content

Abduction with Negation as Failure for Active and Reactive Rules

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1792))

Abstract

Recent work has suggested abductive logic programming as a suitable formalism to represent active databases and intelligent agents. In particular, abducibles in abductive logic programs can be used to represent actions, and integrity constaints in abductive logic programs can be used to represent active rules of the kind encountered in active databases and reactive rules incorporating reactive behaviour in agents. One would expect that, in this approach, abductive proof procedures could provide the engine underlying active database management systems and the behaviour of agents. We analyse existing abductive proof procedures and argue that they are inadequate in handling these applications. The inadequacy is due to the inappropriate treatment of negative literals in integrity constraints. We propose a new abductive proof procedure and give examples of how this proof procedure can be used to achieve active behaviour in (deductive) databases and reactivity in agents. Finally, we prove some soundness and completeness results for the new proof procedure.

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. Clark, K.L.; 1978. Negation as failure. Logic and Data Bases, 293–322, Plenum, NY.

    Google Scholar 

  2. Console, L.; Theseider Dupré, D.; Torasso, P.; 1991. On the relationship between abduction and deduction. Journal of Logic and Computation 2(5): 661–690, OUP.

    Article  Google Scholar 

  3. Denecker, M.; De Schreye, D.; 1997. SLDNFA: an abductive procedure for abductive logic programs. Journal of Logic Programming 34(2): 111–167, Elsevier.

    Article  Google Scholar 

  4. Dung, P.M.; Mancarella, P.; 1996. Production systems need negation as failure. Proc. 13th AAAI, AAAI Press.

    Google Scholar 

  5. Fung, T.H.; Kowalski, R.A.; 1997. The iff procedure for abductive logic programming. Journal of Logic Programming 33(2):151–165, Elsevier.

    Article  MATH  MathSciNet  Google Scholar 

  6. Gelfond, M.; Lifschitz, V.; 1988. The stable model semantics for logic programming. Proc. 5th ICLP 1070–1080, MIT Press.

    Google Scholar 

  7. Huhns, M.N.; Singh M.P. (eds); 1997. Readings in Agents, Morgan Kaufman.

    Google Scholar 

  8. Inoue, K.; Koshimura, M.; Hasegawa, R.; 1992. Embedding negation as failure into a model generation theorem prover. Proc. 11th CADE, LNAI 607:400–415, Springer.

    Google Scholar 

  9. Kakas, A.C.; Kowalski, R.A.; Toni, F.; 1998. The role of abduction in logic programming. Handbook of Logic in AI and Logic Programming 5:235–324, OUP.

    MathSciNet  Google Scholar 

  10. Kakas, A.C.; Mancarella, P.; 1990. Abductive Logic Programming. Workshop on Non-Monotonic Reasoning and Logic Programming.

    Google Scholar 

  11. Kowalski, R.A.; Sadri, F.; 1999. From Logic Programming to Multi-agent Systems. Annals of Mathemathics and Artificial Intelligence (Forthcoming).

    Google Scholar 

  12. Kowalski, R.A.; Toni, F.; Wetzel, G.; 1998. Executing suspended logic programs. Fundamenta Informaticae 34(3):203–224, ISO Press.

    MATH  MathSciNet  Google Scholar 

  13. Martelli, A.; Montanari, U.; 1982. An efficient unification algorithm. ACM Trans. on Prog. Lang. and Systems 4(2):258–282.

    Article  MATH  Google Scholar 

  14. Poole, D.; 1988. A logical framework for default reasoning. Artificial Intelligence 36:27–47, Elsevier.

    Article  MATH  MathSciNet  Google Scholar 

  15. Rao, A.S.; Georgeff, M.P.; 1992. An abstract architecture for rational agents. Proc. 3rd Int. Conf. on Principles of Knowledge Representation and Reasoning.

    Google Scholar 

  16. Shanahan, M.; 1997. Event calculus planning revisited. Proc. 4th European Conference on Planning 390–402, LNAI 1348, Springer.

    Google Scholar 

  17. Widom, J.; Ceri, S.; 1996. Active Database Systems: Triggers and Rules for Advanced Database Processing, Morgan Kaufmann.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2000 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Sadri, F., Toni, F. (2000). Abduction with Negation as Failure for Active and Reactive Rules. In: Lamma, E., Mello, P. (eds) AI*IA 99: Advances in Artificial Intelligence. AI*IA 1999. Lecture Notes in Computer Science(), vol 1792. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46238-4_5

Download citation

  • DOI: https://doi.org/10.1007/3-540-46238-4_5

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67350-7

  • Online ISBN: 978-3-540-46238-5

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics