skip to main content
10.1145/98894.99106acmconferencesArticle/Chapter ViewAbstractPublication Pagesiea-aeiConference Proceedingsconference-collections
Article
Free Access

Learning apprentice system for turbine modelling

Authors Info & Claims
Published:01 June 1990Publication History

ABSTRACT

A learning apprentice system is presented, which learns from examples extracted from user dialogues. The system provides an interface between the user and the turbine modeller. While a dialogue is carried out between the user and the turbine modelling software, the system observes the dialogues and whenever a new example is observed which performs a task completely, the system tries to learn it. The learning methodology used by the system is described and various drawbacks are pointed out. A new learning methodology is proposed which easily overcomes the problems faced by the earlier methodology.

References

  1. Carpineto_88.Claudio Carpineto, "An Approach Based on Integrated ~g to Generating Stories From Stories," in Proceedings of Fifth International Conference on Machine Learning, pp. 298-304, June, 1988.Google ScholarGoogle Scholar
  2. Danyluk_87.Andres Pohoreckyj Danyluk, "The Use of Explanations for Similarity-based Learning," in Proceedings of Tenth IJCAI, pp. 274-276, August, 1987.Google ScholarGoogle Scholar
  3. DeJong_81.Gerald DeJong, "Generalizations Based on Explanations," in Proceedings of lJCA181, pp. 67-69, 1981.Google ScholarGoogle Scholar
  4. DeJong_83.Gerald DeJong, "Acq~g Schemeta Through Understanding and Generalizing Plans," in Proceedings of IJCA183, pp. 462-464, 1983.Google ScholarGoogle Scholar
  5. DeJong_86a.Gerald DeJong and Raymond Mooney, "Explanation- Based Learning: An Alternative View," Machine Learning, vol. i, no. 2, pp. 145-176, 1986. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. DeJong_86b.Gerald De$ong, "A Brief Overview of Explanatory Schema Acquisition"," in Machine Learning' A Guide to Current Research, ed. T.M Mitchell, R.S. Michalski and J.G. Carbonell, pp. 47-50, 1986. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Ellman_85.Thomas Ellman, "Generalizing Logic Circuit Designs by Analyzing Proofs of Correction," in Proceedings of lJCAl 85, pp. 643-646, August 18-23, 1985.Google ScholarGoogle Scholar
  8. Ellman_86.Thomas Ellman, "Explanation Based Learning in Logic Circuit Design," in Machine Learning: A Guide to Current Research, ed. T. M. Mitchell, J. G. Carbonell and R. S. Michalski, pp. 63-66, 1986. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Fikes_72.Richard E. Fikes, Peter E. Hart, and Nils I. Nilsson, "Learning and Executing Generalized Robot Plans," Artificial Intelligence, vol. 3, pp. 251-288, 1972.Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Fisher_87.Douglas H. Fisher, "Knowledge Acquisition Via Incremental Conceptual Clustering," Machine Learning, vol. 2, no. 2, pp. 139-172, 1987. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Iba_88.Wayne Iba, lames Wogulis, and Pat Langley, "Trading Off Simplicity and Coverage in Incremental Concept Learning," in Proceedings of the Fifth international Conference on Machine Learning, pp. 73-79, June, 1988.Google ScholarGoogle Scholar
  12. Kedar-Cabelli_87.Smadar Tova Kedar-CabeUi and L. T. McCarty, "Explanation-Based Generalization as Resolution Theorem Proving," in Proceedings of The Fourth International Workshop on Machine Learning, pp. 383- 389, June, 1987.Google ScholarGoogle Scholar
  13. Kedar-Cabelli_88.Smadar Tova Kedar-CabeUi, "Formulating Concepts and Analogies According to Purpose," Ph.D. Dissertation, Dept. of Computer Science, Rutgers University, NJ, May 1988.Google ScholarGoogle Scholar
  14. Kodratoff_88.Yves Kodratoff, Introduction To Machine Learning, Pitman Publishing, 128 Long Acre, London WC2E 9AN, 1988.Google ScholarGoogle Scholar
  15. Lebowitz_83.Michael Lebowitz, "RESEARCHER: An Overview," in Proceedings of AAAI-83, pp. 232-235, 1983.Google ScholarGoogle Scholar
  16. Lebowitz_86.Michael Lebowitz, "Concept Learning in a Rich Input Domain: Genexalization Based Memo~," in Machine Learning.' An Artificial Intelligence Approach Volume II, ed. R, S. Michalski, J. G. Carbonell and T. M. Mitchell, pp. 193-214, Morgan Kaufman Publishers, Inc, 1986.Google ScholarGoogle Scholar
  17. Lebowitz_87.Michael Lebowitz, "Experiments With Incremental Concept Formation: UNIMEM," Machine Learning, vol. 2, no. 2, pp. 103-138, 1987. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Mitchell_83.Tom M. Mitchell, Louis i. Steinberg, Smadar Kedar- Cabelli, Van E. Kelly, Jeffrey Shulman, and Timothy Weinfich, "An Intelligent Aid for Circuit Redesign," in Proceedings of AAAI-83, pp. 274-278, 1983.Google ScholarGoogle Scholar
  19. Mitchell_85.Tom M. Mitchell, Sridhar Mahadevan, and Louis i. Steinberg, "LEAP' A Learning Apprentice for VLSI Design," in Proceedings of Ninth IJCAI, pp. 573-580, 1985.Google ScholarGoogle Scholar
  20. Mitchell_86a.Tom M. Mitchell, Sridhar Mahadevan, and Louis I. Steinberg, "A Le~g Apprentice System for VLSI Design," in Machine Learning: A Guide to Current Research, ed. T. M. Mitchell J. G. Carbonell and R. S. Michalski, pp. 203-206, 1986. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Mitchell_86b.Tom M. Mitchell Richard M. Keller, and Smadar T. Kedar-Cabelli, "Explanation-Based Generalization: A Unifying View," Machine Learning, vol. 1, no. 1, pp. 47- 80, 1986. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Mooney_86.Raymond J. Mooney and Scott W. Bennett, "A Domain Independent Explanation Based Generalizer," in Proceedings of AAAI-86, pp. 551-555, 1986.Google ScholarGoogle Scholar
  23. Pazzani_88a.Michael J. Pazzani, "Explanation Based ~g for Knowledge Based Systems," in Knowledge Acquisition for Knowledge Based Systems, ed. B. Gaines and J. Boose, vol. 1, pp. 217-237, 1988.Google ScholarGoogle Scholar
  24. Pazzani_88b.Michael J. Pazzani, "Integrated Learning with Incorrect and Incomplete Theories," in Proceedings of Fifth International Corqeerence on Machine Learning, pp. 291- 297, June, 1988.Google ScholarGoogle Scholar
  25. Silver_83.Bernard Silver, "Learning Equation Solving Methods From Examples," in Proceedings of iJCAI 83, pp. 429- 431, 1983.Google ScholarGoogle Scholar
  26. Silver_86.Bernard Silver, "Precondition Analysis: Learning Control information," in Machine Learning: An Artificial intelligence Approach Volume II, ed. R. S. Michalski, J. G. Carbonell and T. M. Mitchell, pp. 647-670, Morgan Kaufman Publishers, 1986.Google ScholarGoogle Scholar
  27. Thomas_72.G. B. Thomas, "Rotordynamics," in lnst Mech Eng Cortf, Vibrations in Rotating Systems, 1972.Google ScholarGoogle Scholar
  28. Thomas_88.O. B. Thomas, R. C. Thomas, and C. C. Lai, "An Expert System Interface to a Suit of Rotordynamics Programs," in Fourth International Conference on Vibrations in rotating machinery, pp. 621-625, Herriot-Watt University, September, 1988.Google ScholarGoogle Scholar
  29. Thomas_90.R. C. Thomas, G. B. Thomas, and J. G. Littler, "The Cognitive Role of an Engineer in a Diagnostic Task," in Proceedings of UKI790 Conference, Southampton, March, 1990.Google ScholarGoogle Scholar

Index Terms

  1. Learning apprentice system for turbine modelling

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Conferences
          IEA/AIE '90: Proceedings of the 3rd international conference on Industrial and engineering applications of artificial intelligence and expert systems - Volume 2
          June 1990
          591 pages
          ISBN:0897913728
          DOI:10.1145/98894

          Copyright © 1990 ACM

          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 1 June 1990

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • Article
        • Article Metrics

          • Downloads (Last 12 months)3
          • Downloads (Last 6 weeks)2

          Other Metrics

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader