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Deductive plan generation

  • Wolfgang Bibel
  • Michael Thielscher
Invited Talks Analogical and Inductive Inference
Part of the Lecture Notes in Computer Science book series (LNCS, volume 872)

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References

  1. 1.
    C. Baral and M. Gelfond. Representing Concurrent Actions in Extended Logic Programming. In R. Bajcsy, editor, Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), pages 866–871, Chambéry, August 1993. Morgan Kaufmann.Google Scholar
  2. 2.
    W. Bibel. A Deductive Solution for Plan Generation. New Generation Computing, 4:115–132, 1986.Google Scholar
  3. 3.
    W. Bibel. A Deductive Solution for Plan Generation. In J. W. Schmidt and C. Thanos, editors, Foundations of Knowledge Base Management, pages 453–473. Springer, 1989.Google Scholar
  4. 4.
    W. Bibel, L. F. del Cerro, B. Fronhöfer, and A. Herzig. Plan generation by linear proofs: on semantics. In Proceedings of the German Workshop on Artificial Intelligence, pages 49–62. Springer, Informatik Fachberichte 216, 1989.Google Scholar
  5. 5.
    S.-E. Bornscheuer and M. Thielscher. Representing Concurrent Actions and Solving Conflicts. In L. Drechler-Fischer and B. Nebel, editors, Proceedings of the German Annual Conference on Artificial Intelligence (KI), Saarbrücken, September 1994. Springer-Verlag. (Selected Paper).Google Scholar
  6. 6.
    S. Brüning, S. Hölldobler, J. Schneeberger, U. Sigmund, and M. Thielscher. Disjunction in Resource-Oriented Deductive Planning. In D. Miller, editor, Proceedings of the International Logic Programming Symposium (ILPS), page 670, Vancouver, October 1993. MIT Press. (Poster).Google Scholar
  7. 7.
    S. Brüning, S. Hölldobler, J. Schneeberger, U. Sigmund, and M. Thielscher. Disjunction in Resource-Oriented Deductive Planning. Technical Report AIDA-94-03, Intellektik, TH Darmstadt, March 1994. Available by anonymous ftp from 130.83.26.1 in pub/AIDA/Tech-Reports/1994Google Scholar
  8. 8.
    M. Gelfond and V. Lifschitz. Representing Action and Change by Logic Programs. Journal of Logic Programming, 17:301–321, 1993.Google Scholar
  9. 9.
    J.-Y. Girard. Linear Logic. Journal of Theoretical Computer Science, 50(1):1–102, 1987.Google Scholar
  10. 10.
    C. Green. Application of theorem proving to problem solving. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), pages 219–239, Los Altos, CA, 1969. Morgan Kaufmann Publishers.Google Scholar
  11. 11.
    G. Große, S. Hölldobler, and J. Schneeberger. Linear Deductive Planning. Logic and Computation, 1994. (To appear).Google Scholar
  12. 12.
    G. Große, S. Hölldobler, J. Schneeberger, U. Sigmund, and M. Thielscher. Equational Logic Programming, Actions, and Change. In K. Apt, editor, Proceedings of the International Joint Conference and Symposium on Logic Programming (IJC-SLP), pages 177–191, Washington, 1992. MIT Press.Google Scholar
  13. 13.
    S. Hölldobler. On Deductive Planning and the Frame Problem. In A. Voronkov, editor, Proceedings of the International Conference on Logic Programming and Automated Reasoning (LPAR), volume 624 of LNAI, pages 13–29. Springer-Verlag, July 1992.Google Scholar
  14. 14.
    S. Hölldobler and J. Schneeberger. A New Deductive Approach to Planning. New Generation Computing, 8:225–244, 1990.Google Scholar
  15. 15.
    S. Hölldobler and M. Thielscher. Actions and Specificity. In D. Miller, editor, Proceedings of the International Logic Programming Symposium (ILPS), pages 164–180, Vancouver, October 1993. MIT Press.Google Scholar
  16. 16.
    S. Hölldobler and M. Thielscher. Computing Change and Specificity with Equational Logic Programs. Annals of Mathematics and Artificial Intelligence, special issue on Processing of Declarative Knowledge, 1994. (To appear).Google Scholar
  17. 17.
    R. Kowalski. Logic for Problem Solving, volume 7 of Artificial Intelligence Series. Elsevier, 1979.Google Scholar
  18. 18.
    M. Masseron, C. Tollu, and J. Vauzielles. Generating Plans in Linear Logic. In Foundations of Software Technology and Theoretical Computer Science, volume 472 of LNCS, pages 63–75. Springer-Verlag, 1990.Google Scholar
  19. 19.
    J. McCarthy. Applications of circumscription to formalizing common-sense knowledge. Artificial Intelligence Journal, 28:89–116, 1986.Google Scholar
  20. 20.
    J. McCarthy and P. J. Hayes. Some Philosophical Problems from the Standpoint of Artificial Intelligence. Machine Intelligence, 4:463–502, 1969.Google Scholar
  21. 21.
    E. Sandewall. Features and Fluents. Technical Report LiTH-IDA-R-92-30, Institutionen för datavetenskap, Universitetet och Tekniska högskolan i Linköping, Schweden, 1992.Google Scholar
  22. 22.
    E. Sandewall. The range of applicability of nonmonotonic logics for the inertia problem. In R. Bajcsy, editor, Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), pages 738–743, Chambéry, France, August 1993. Morgan Kaufmann.Google Scholar
  23. 23.
    J. Schneeberger. Plan Generation by Linear Deduction. PhD thesis, FG Intellektik, TH Darmstadt, 1992.Google Scholar
  24. 24.
    M. Thielscher. An Analysis of Systematic Approaches to Reasoning about Actions and Change. In P. Jorrand, editor, International Conference on Artificial Intelligence: Methodology, Systems, Applications (AIMSA), Sofia, Bulgaria, September 1994. World Scientific Publishing Co.Google Scholar
  25. 25.
    M. Thielscher. Representing Actions in Equational Logic Programming. In P. Van Hentenryck, editor, Proceedings of the International Conference on Logic Programming (ICLP), pages 207–225, Santa Margherita Ligure, Italy, 1994. MIT Press.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1994

Authors and Affiliations

  • Wolfgang Bibel
    • 1
  • Michael Thielscher
    • 1
  1. 1.FG Intellektik, FB InformatikTechnische Hochschule DarmstadtDarmstadtGermany

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