Skip to main content

A terminological qualification calculus for preferential reasoning under uncertainty

  • Conference paper
  • First Online:
KI-96: Advances in Artificial Intelligence (KI 1996)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1137))

Included in the following conference series:

Abstract

We introduce a qualitative model of uncertain reasoning and illustrate its application in the framework of a natural language understanding task. Considering uncertain reasoning as a preferential choice problem between alternative hypotheses, the model we provide assigns quality labels to single evidences for or against a hypothesis, combines the generated labels in terms of the overall credibility of a single hypothesis, and, finally, computes a preference order on the entire set of competing hypotheses. This model of quality-based uncertain reasoning is entirely embedded in a terminological logic framework.

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

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. S. Buvač, V. Buvač, and I. Mason. Metamathematics of contexts. Fundamenta Informaticae, 23(3), 1995.

    Google Scholar 

  2. P. Cohen. Heuristic Reasoning about Uncertainty: An Artificial Intelligence Approach. Los Altos/CA: Morgan Kaufmann, 1985.

    Google Scholar 

  3. P. Cohen. The control of reasoning under uncertainty: a discussion of some programs. In G. Shafer and J. Pearl, editors, Readings in Uncertain Reasoning, pages 177–197. San Mateo/CA: Morgan Kaufmann, 1990.

    Google Scholar 

  4. J. Fox and P. Krause. Symbolic decision theory and autonomous systems. In B. D'Ambrosio, P. Smets, and P. Bonissone, editors, UAI'91 — Proc. 7th Conf. on Uncertainty in Artificial Intelligence, pages 103–110. San Mateo/CA: Morgan Kaufmann, 1991.

    Google Scholar 

  5. U. Hahn, M. Klenner, and K. Schnattinger. Learning from texts — a terminological metareasoning perspective. In S. Wermter, E. Riloff, and G. Scheler, editors, Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing, pages 453–468. Berlin: Springer, 1996.

    Google Scholar 

  6. U. Hahn, M. Klenner, and K. Schnattinger. A quality-based terminological reasoning model for text knowledge acquisition. In N. Shadbolt, K. O'Hara, and G. Schreiber, editors, EKAW'96 — Proc. 9th European Knowledge Acquisition Workshop, pages 131–146. Berlin: Springer, 1996.

    Google Scholar 

  7. U. Hahn, S. Schacht, and N. Bröker. Concurrent, object-oriented dependency parsing: the ParseTalk model. International Journal of Human-Computer Studies, 41(1–2): 179–222, 1994.

    Google Scholar 

  8. B. Heinsohn. Probabilistic description logics. In R. Lopez de Mantaras and D. Poole, editors, UAI'94 — Proc. 10th Conf. on Uncertainty in Artificial Intelligence, pages 311–318. San Mateo/CA: Morgan Kaufmann, 1994.

    Google Scholar 

  9. J. Hobbs, M. Stickel, D. Appelt, and P. Martin. Interpretation as abduction. Artificial Intelligence, 63(1–2):69–142, 1993.

    Google Scholar 

  10. B. Hollunder. An alternative proof method for possibilistic logic and its application to terminological logics. In R. Lopez de Mantaras and D. Poole, editors, UAI'94 — Proc. 10th Conf. on Uncertainty in Artificial Intelligence, pages 327–335. San Mateo/CA: Morgan Kaufmann, 1994.

    Google Scholar 

  11. M. Jaeger. Probabilistic reasoning in terminological logics. In J. Doyle, E. Sandewall, and P. Torasso, editors, KR'94 — Proc. 4th International Conf. on Principles of Knowledge Representation and Reasoning, pages 305–316. San Mateo/CA: Morgan Kaufmann, 1994.

    Google Scholar 

  12. M. Klenner and U. Hahn. Concept versioning: a methodology for tracking evolutionary concept drift in dynamic concept systems. In A. Cohn, editor, ECAI'94 — Proc. 11th European Conf. on Artificial Intelligence, pages 473–477. Chichester: J. Wiley, 1994.

    Google Scholar 

  13. P. Krause, S. Ambler, M. Elvang-Goransson, and J. Fox. A logic of argumentation for reasoning under uncertainty. Computational Intelligence, 11:113–131, 1995.

    Google Scholar 

  14. R. MacGregor. A description classifier for the predicate calculus. In AAAI'94 — Proc. 12th National Conf. on Artificial Intelligence. Vol. 1, pages 213–220. Menlo Park: AAAI Press/M.I.T. Press, 1994.

    Google Scholar 

  15. J. McCarthy. Notes on formalizing context. In IJCAI'93 — Proc. 13th International Joint Conf. on Artificial Intelligence. Vol. 1, pages 555–560. San Mateo/CA: Morgan Kaufmann, 1993.

    Google Scholar 

  16. P. Neuhaus and U. Hahn. Trading off completeness for efficiency: the ParseTalk performance grammar approach to real-world text parsing. In FLAIRS'96 — Proc. 9th Florida Artificial Intelligence Research Symposium, pages 60–65. Florida AI Research Society, 1996.

    Google Scholar 

  17. D. Pacholczyk. Qualitative reasoning under uncertainty. In C. Pinto-Ferreira and N. Mamede, editors, Progress in Artificial Intelligence. EPIA '95 — Proc. 7th Portuguese Conf. on Artificial Intelligence, pages 297–309. Berlin: Springer, 1995.

    Google Scholar 

  18. J. Quantz. Interpretation as exception minimization. In IJCAI'93 — Proc. 13th International Joint Conf. on Artificial Intelligence. Vol. 2, pages 1310–1315. San Mateo/CA: Morgan Kaufmann, 1993.

    Google Scholar 

  19. K. Schnattinger, U. Hahn, and M. Klenner. Quality-based terminological reasoning for concept learning. In I. Wachsmuth, C.-R. Rollinger, and W. Brauer, editors, Advances in Artificial Intelligence. KI'95 — Proc. 19th Annual German Conf. on Artificial Intelligence, pages 113–124. Berlin: Springer, 1995.

    Google Scholar 

  20. K. Schnattinger, U. Hahn, and M. Klenner. Terminological meta-reasoning by reification and multiple contexts. In C. Pinto-Ferreira and N. Mamede, editors, Progress in Artificial Intelligence. EPIA'95 — Proc. 7th Portuguese Conf. on Artificíal Intelligence, pages 1–16. Berlin: Springer, 1995.

    Google Scholar 

  21. G. Shafer and J. Pearl, editors. Readings in Uncertain Reasoning. San Mateo/CA: Morgan Kaufmann, 1990.

    Google Scholar 

  22. W. Woods and J. Schmolze. The KL-ONE family. Computers & Mathematics with Applications, 23(2–5): 133–177, 1992.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Günther Görz Steffen Hölldobler

Rights and permissions

Reprints and permissions

Copyright information

© 1996 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Schnattinger, K., Hahn, U. (1996). A terminological qualification calculus for preferential reasoning under uncertainty. In: Görz, G., Hölldobler, S. (eds) KI-96: Advances in Artificial Intelligence. KI 1996. Lecture Notes in Computer Science, vol 1137. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61708-6_76

Download citation

  • DOI: https://doi.org/10.1007/3-540-61708-6_76

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61708-2

  • Online ISBN: 978-3-540-70669-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics