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Generation and Explanation: Building an Explanation Facility for the Explainable Expert Systems Framework

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Natural Language Generation in Artificial Intelligence and Computational Linguistics

Part of the book series: The Kluwer International Series in Engineering and Computer Science ((SECS,volume 119))

Abstract

Generating explanations for expert systems has not been seen as a sophisticated generation problem in the past, and researchers working on expert system explanations (mainly researchers working on expert systems themselves) have been largely separated from the natural language generation community. In this paper, we argue that explanation for expert systems can benefit from the more sophisticated generation techniques being developed in computational linguistics and that explanation for expert systems actually provides a rich domain in which to study natural language generation. We describe our efforts to build a generation facility for the Explainable Expert Systems (EES) framework, presenting the requirements for this generation task and the issues addressed. We initially tried to use known natural language generation techniques but were led to design a new text planner, as these techniques did not fit our needs. This paper thus presents an overview of the generation facility being built for EES, including an ‘historical’ perspective that explains the decisions we made. Finally, we briefly present directions for future research.

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Bibliography

  1. Douglas E. Appelt. Planning Natural Language Utterances. Cambridge University Press, Cambridge, England, 1985.

    Google Scholar 

  2. John A. Bateman and Cécile L. Paris. Phrasing a text in terms the user can understand. In Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, Detroit, Michigan, 1989.

    Google Scholar 

  3. Bruce G. Buchanan and E. H. Shortliffe. Rule-Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project. Addison-Wesley Publishing Company, Reading, Mass., 1984.

    Google Scholar 

  4. Yee Han Cheong and Ingrid Zukerman. Enhancing automatically generated explanations by means of rhetorical devices, 1988. Dept of Computer Science, Monash University, Clayton, Victoria 3168, Australia.

    Google Scholar 

  5. William Clancey. NEOMYCIN: Reconfiguring a rule-based expert system for application to teaching. Technical report, IJCAI, Vancouver, BC, August 1981.

    Google Scholar 

  6. William Clancey. The epistemology of a rule-based expert sys¬tem: A framework for explanation. Artificial Intelligence, 20(3):215–251, 1983. Also in Rule-Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Heuristic Programming Project; Buchanan and Shortliffe (eds), Addison-Wesley, 1984.

    Google Scholar 

  7. Robin Cohen and Marlene Jones. Incorporating user models into expert systems for educational diagnosis. In Alfred Kobsa and Wolfgang Wahlster, editors, User Models in Dialog Systems. Springer Verlag, Symbolic Computation Series, Berlin Heidelberg New York Tokyo, 1987.

    Google Scholar 

  8. P. R. Cohen and C. R. Perrault. Elements of a plan-based theory of speech acts. Cognitive Science, 3:pages 177 — 212, 1979.

    Google Scholar 

  9. G. Nigel Gilbert. Forms of explanation, August 1988. Presented at the AAAI-88 Workshop on Explanations.

    Google Scholar 

  10. H. P. Grice. Logic and conversation. In P. Cole and J. L. Morgan, editors, Syntax and Semantics. Academic Press, New York, 1975.

    Google Scholar 

  11. Eduard H. Hovy. Approaches to the planning of coherent text, July 1988. To appear in selected papers from The 4th International Workshop on text generation Catalina, California. Edited by Paris, C., Swartout, W., and Mann, W.

    Google Scholar 

  12. Eduard H. Hovy. Planning coherent multisentential texts. In The Proceedings of the 26th. Annual Meeting of the Association of Computational Linguistics, pages 163 — 169. Association for Computational Linguistics, June 1988.

    Google Scholar 

  13. Karen Kukich. Explanation structures in XSEL. In Proceedings of the 23rd Annual Meeting of the Association for Computational Linguistics, Chicago, Illinois, 1985. Association for Computational Linguistics.

    Google Scholar 

  14. William Mann and Sandra Thompson. Rhetorical structure theory: a theory of text organization. In Livia Polanyi, editor, The Structure of Discourse. Ablex Publishing Corporation, Norwood, New Jersey, 1987. Also available as USC/Information Sciences Institute Technical Report Number RS-87–190.

    Google Scholar 

  15. William C. Mann. Discourse structure for text generation. Technical Report ISI/RR-84–127, Information Sciences Institute, February 1984. 4676 Admiralty Way, Marina del Rey, California 90292–6695.

    Google Scholar 

  16. Mark Maybury. Explanation rhetoric: The rhetorical progression of justifications, 1988. Rome Air Development Center, Griffiss AFB, Rome NY 13441–5700.

    Google Scholar 

  17. Kathleen F. McCoy. The ROMPER system: Responding to object-related misconceptions using perspective. In Proceedings of the 24th Annual Meeting of the ACL, New York City, New York, June 1986. Association of Computational Linguistics.

    Google Scholar 

  18. Kathleen F. McCoy. Reasoning on a dynamically highlighted user model to respond to misconceptions. Computational Linguistics, 14 (3), September 1988.

    Google Scholar 

  19. Kathleen R. McKeown, Michael Wish, and Kevin Matthews. Tailoring explanations for the user. In Proceedings of IJCAI-85,Los Angeles, Ca., 1985. International Joint Conference on Artificial Intelligence.

    Google Scholar 

  20. Kathleen R. McKeown. Text Generation: Using Discourse Strategies and Focus Constraints to Generate Natural Language Text. Cambridge University Press, Cambridge, England, 1985.

    Google Scholar 

  21. Johanna D. Moore and Cécile L. Paris. Constructing coherent texts using rhetorical relations. In Proceedings of the Tenth Annual Conference of the Cognitive Science Society. Cognitive Science Society, August 1988.

    Google Scholar 

  22. Johanna D. Moore and William R. Swartout. A reactive approach to explanation, August 1988. Presented at the AAAI Workshop on Explanations.

    Google Scholar 

  23. Johanna D. Moore and William R. Swartout. A reactive approach to explanation, July 1988. To appear in selected papers from The Ph International Workshop on text generation Catalina, California. Edited by Paris, C., Swartout, W., and Mann, W.

    Google Scholar 

  24. Cécile L. Paris and Kathleen R. McKeown. Discourse strategies for describing complex physical objects. In G. Kern-pen, editor, Natural Language Generation: Recent Advances in Artificial Intelligence, Psychology, and Linguistics. Kluwer Academic Publishers, Boston/Dordrecht, 1987. Paper presented at the Third International Workshop on Natural Language Generation, August 1986, Nijmegen, The Netherlands.

    Google Scholar 

  25. Cécile L. Paris. Description strategies for naive and expert users. In Proceedings of the 23rd Annual Meeting of the Association for Computational Linguistics, Chicago, 1985.

    Google Scholar 

  26. Cécile L. Paris. The Use of Explicit User Models in Text Generation: Tailoring to a User’s Level of Expertise. PhD thesis, Columbia University Department of Computer Science, 1987. To be published in the “Communication in Artificial Intelligence” series, Steiner and Fawcett (eds), Frances Pinter, 1990.

    Google Scholar 

  27. Cécile L. Paris. Planning a text: can we and how should we modularize this process?, August 1988. Presented at the AAAI-88 Workshop on Text Planning and Realization.

    Google Scholar 

  28. Cécile L. Paris. Tailoring Object Descriptions to the User’s Level of Expertise. Computational Linguistics, 14 (3):64–78, September 1988. Special Issue on User Modeling.

    Google Scholar 

  29. Cécile L. Paris. The Use of Explicit User Models in a Generation System for Tailoring Answers to the User’s Level of Expertise. In Alfred Kobsa and Wolfgang Wahlster, editors, User Models in Dialog Systems. Springer Verlag, Symbolic Computation Series, Berlin Heidelberg New York Tokyo, 1989.

    Google Scholar 

  30. Martha Pollack, Julia Hirschberg, and Bonnie Webber. User participation in the reasoning processes of expert systems. In Proceedings of the AAAI,Pittsburgh, Pa, 1982. American Association of Artificial Intelligence.

    Google Scholar 

  31. Ivan Rankin, Sture Hagglund, and Yvonne Waern. Generating user-centered explanations in a critiquing context, August 1988. Presented at the AAAI Workshop on Explanations.

    Google Scholar 

  32. Earl Sacerdoti. A Structure for Plans and Behavior. American Elsevier North-Holland, New York, 1977.

    MATH  Google Scholar 

  33. Dan Suthers. Providing multiple views of reasoning for expla- nations, August 1988. Presented at the AAAI Workshop on Explanations.

    Google Scholar 

  34. William Swartout and Steve W. Smoliar. Explaining the link between causal reasoning and expert behavior. In Proceedings of the Symposium on Computer Applications in Medical Care,Washington, D. C., November 1987. also to appear in “Topics in Medical Artificial Intelligence”; Miller, P.L. (ed), Springer-Verlag.

    Google Scholar 

  35. William R. Swartout and Steve W. Smoliar. On making expert systems more like experts. Expert Systems, 4 (3), August 1987.

    Google Scholar 

  36. William Swartout. XPLAIN: A System for Creating and Explaining Expert Consulting Systems. Artificial Intelligence,21(3):285–325, September 1983. Also available as ISI/RS-83–4.

    Google Scholar 

  37. William R. Swartout. Explaining and justifying expert consulting programs. In Readings in Medical Artificial Intelligence: The First Decade. Addison-Wesley, 1984. Reprinted from Proceedings of the Seventh International Joint Conference on Artificial Intelligence, 1981.

    Google Scholar 

  38. William Swartout. Knowledge Needed for Expert System Explanation. In AFIPS Conference Proceedings, volume 54, pages 93–98. National Computer Conference, 1985.

    Google Scholar 

  39. Michael C. Tanner and John R. Josephson. Justifying diagnostic conclusions, August 1988. Presented at the AAAI-88 Workshop on Explanations.

    Google Scholar 

  40. R. L. Teach and E. H. Shortliffe. An analysis of physicians’ attitudes. In Rule-Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project. Addison-Wesley Publishing Company, Reading, Mass., 1984.

    Google Scholar 

  41. Peter van Beek. A model for generating better explanations. In Proceedings of the 25th Annual Meeting of the ACL,Palo Alto, California, 1987. Association of Computational Linguistics.

    Google Scholar 

  42. J.W. Wallis and E.H. Shortliffe. Explanatory power for medical expert systems: Studies in the representation of causal relationships for clinical consultation. Technical Report STAN-CS-82–923, Stanford University, 1982. Heuristics Programming Project. Department of Medecine and Computer Science.

    Google Scholar 

  43. J. Weiner. Blah, a system that explains its reasoning. Artificial Intelligence Journal, 15:19 — 48, 1980.

    Google Scholar 

  44. R. L. Wexelblat. The confidence in their help, August 1988. Presented at the AAAI-88 Workshop on Explanations.

    Google Scholar 

  45. M.R. Wick and W.B. Thompson. Reconstructive Explanation: Explanation as Complex Problem Solving In Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, Detroit, Michigan, 1989.

    Google Scholar 

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Paris, C.L. (1991). Generation and Explanation: Building an Explanation Facility for the Explainable Expert Systems Framework. In: Paris, C.L., Swartout, W.R., Mann, W.C. (eds) Natural Language Generation in Artificial Intelligence and Computational Linguistics. The Kluwer International Series in Engineering and Computer Science, vol 119. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-5945-7_2

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  • DOI: https://doi.org/10.1007/978-1-4757-5945-7_2

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4419-5125-0

  • Online ISBN: 978-1-4757-5945-7

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