Skip to main content

Abstract

Artificial Intelligence and its subfield Expert Systems have reached a level of maturity, particularly in recent years, and have evolved to the point that a Knowledge-Based Expert System may reach a level of performance comparable to that of a human expert in specialized problem domains like, Computer Systems, Computing, Education, Engineering, Knowledge Engineering, Geology, Medicine and Science. An Expert System is a high performance problem solving (software) computer program, capable of simulating human expertise in a narrow domain.

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

Access this chapter

eBook
USD 16.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

Bibliography

  1. Beale, G.O. and Kawamura, K., “Coupling symbolic and numerical computation for intelligent simulation,” in Knowledge-Based System Diagnosis, Supervision and Control, (S. Tzafestas, Ed.), Plenum, New-York-London (Ch. 8), 1989.

    Google Scholar 

  2. Bobrow, D.G. and Collins, A., Eds., Representations and Understanding, New York, Academic Press, 1975.

    Google Scholar 

  3. Bobrow, D.G. and Winograd, T., “An overview of KRL, a knowledge representation language,” Cognitive Science, 1 (1), 1977.

    Google Scholar 

  4. Boose, J.H. and Gaines, B. R., “Knowledge acquisition tools for expert systems,” In: Knowledge Acquisition Tools for Expert Systems, 2. London: Academic Press, 1988.

    Google Scholar 

  5. Brewka, G., “The logic of inheritance in frame systems,” Proceedings of the 10th International Joint Conference on Artificial Intelligence, pp. 438–488, 1987.

    Google Scholar 

  6. Buchanan, B.G. and Feigenbaum, E. A., “DENDRAL and Meta-DENDRAL: Their applications dimension Artificial Intelligence, 11, pp. 5–24, 1978.

    Google Scholar 

  7. Buchanan, B. G., Barstow, D., Bechtel, R., Bennet, J., Clancey, W., Kulkowski, C., Mitchell, T. M. and Waterman, D. A., “Constructing an expert system,” In Hayes-Roth et al., Chapter 5, 1983.

    Google Scholar 

  8. Buchanan, B. G. and Shortliffe, E. H., Rule-Based Expert Systems, Reading MA: Addison-Wesley, 1984.

    Google Scholar 

  9. Clancey, W. J., “Heuristic classification,” Artificial Intelligence, 27, pp. 289–350, 1985.

    Article  Google Scholar 

  10. Clancey, W. J., “Transcript of plenary sessions. Cognition and expertise,” 1st AAAI Workshop Knowledge Acquisition in Knowledge Based Systems, Banff, Canada, 1986.

    Google Scholar 

  11. Deransart, P. and Maluszynski, J., “Relating logic programs and attribute grammars,” J. Logic Programming, 2, pp. 119–155, 1985.

    Article  MATH  MathSciNet  Google Scholar 

  12. Feigenbaum, E. A., “The art of artificial intelligence: Themes and case studies of knowledge engineering,” Proceedings of the 5th International Joint Conference on Artificial Intelligence, pp. 1014–1029, 1977.

    Google Scholar 

  13. Findler, N. V., Associative Networks, Representation and Use of Knowledge by computers, New York, Academic Press, 1979.

    MATH  Google Scholar 

  14. Forbus, K. D., “Qualitative process theory,” Artificial Intelligence, 24, pp. 85–168, 1984.

    Article  Google Scholar 

  15. Forbus, K. D., “The qualitative process engine,” In: Readings in Qualitative Reasoning about Phys ical Systems, (D. S. Weld, J. de Kleer, Eds), Morgan Kaufmann, 1990.

    Google Scholar 

  16. Frost, R., Introduction to Knowledge Based Systems, Collins Professional and Technical Books, 1986.

    Google Scholar 

  17. Gentil, S., Barrand, A. Y. and Szafnicki, K., “SEXI: An expert identification package,” Automatica, 26(4), pp. 803–809, 1990.

    Article  MATH  Google Scholar 

  18. Goedel, K., “On formally undecidable propositions of Principia Mathematica and related systems I,” In Van Heijenoort, pp. 1879–1931, 1967.

    Google Scholar 

  19. Goldberg, A. and Robson, D., Smalltalk 80: the Language and its Implementation, Reading MA: Addison-Wesley, 1983.

    MATH  Google Scholar 

  20. Haest, M., Bastin, G., Geners, M. and Wertz, V., “ESPION: An expert system for system identifi cation,” Automatica, 26(1), pp. 85–95, 1990.

    Article  MATH  MathSciNet  Google Scholar 

  21. Hayes-Roth, B. F., Waterman, D. A. and Lenat, D., Building Expert Systems, Reading MA: Addison-Wesley, 1983.

    Google Scholar 

  22. Hayes-Roth, B. F., “The Knowledge Based Expert System: A Tutorial,” Computer Magazine, 1984.

    Google Scholar 

  23. Hayes-Roth, B. F., “Rule-based systems,” Communications ACM, 26(9), pp. 921–932, 1985.

    Article  Google Scholar 

  24. Horty, J. F., Thomason, R. H. and Touretzky, D. S., “A Skeptical theory of inheritance in non monotonic semantic nets,” Proceedings of the National Conference on Artificial Intelligence, pp. 358–363, 1987.

    Google Scholar 

  25. Jackson, P., Introduction to Expert Systems, Reading MA: Addison-Wesley, 1990.

    Google Scholar 

  26. Jager, R., Verbruggen, H. B., Bruijn, P. M. and Krijgsman, A. J., “Direct real-time control using knowledge-based techniques,” Proc. Europ. Intelligent Simulation Conference, Gent, Belgium, 1990.

    Google Scholar 

  27. Johansen, J. G. and Alty, J. L., “Knowledge engineering for industrial expert systems,” Automatica, 27(1), pp. 97–114, 1991.

    Article  Google Scholar 

  28. Kinnucan, P., Computer that think like experts, High technology, 1984.

    Google Scholar 

  29. Knuth, D. E., “Semantics of context-free languages,” Math. Syst. Theory, 2, pp. 127–145, 1968.

    Article  MATH  MathSciNet  Google Scholar 

  30. Kocabas, S., “A review of learning,” The Knowledge Engineering Review, 6(3), pp. 195–222, 1991.

    Article  Google Scholar 

  31. Kowalski, R. A., Logic for problem solving, Amsterdam: North-Holland, 1979.

    MATH  Google Scholar 

  32. Lenat, D.B., “On automated scientific theory formation: a case study using the AM program,” Machine Intelligence, 9, pp. 251–283, 1979.

    Google Scholar 

  33. Lenat, D. B., “EURISKO: A program that learns new heuristics and domain concepts,” Artificial Intelligence, 21 (1–2), pp. 61–98, 1983.

    Article  Google Scholar 

  34. Lirov, Y., Robing, E. Y., McElhaney, B. G. and Wilburg, L. W., “Artificial Intelligence modelling of control systems,” Simulation, 50(1), pp. 12–24, 1988.

    Article  Google Scholar 

  35. Minsky, M.L. ed., Semantic Information Processing, Cambridge MA: MIT Press, 1968.

    MATH  Google Scholar 

  36. Minsky, M.L., “A framework for representing knowledge,” The Psychology of Computer Vision, pp. 211–277, New York: McGraw-Hill, 1975.

    Google Scholar 

  37. Niwa, K., Sasaki, K. and Ihara, H., “An Experimental Comparison of Knowledge Representation Schemes,” The AI magazine, 5, 29, 1984.

    Google Scholar 

  38. Papakonstantinou, G. and Kontos, J., “Knowledge representation with attribute grammars,” The Computer Journal, 29(3), pp. 241–245, 1986.

    Article  MATH  Google Scholar 

  39. Papakonstantinou, G., Moraitis, C. and Panayiotopoulos, T., “An attribute grammar interpreter as a knowledge engineering tool,” Angewandte Informatik, 9/86, pp. 382–288, 1986.

    Google Scholar 

  40. Papakonstantinou, G. and Tzafestas, S., “Attribute grammar approach to knowledge based system building: Application to fault diagnosis,” In: Knowledge-Based System Diagnosis, Supervision and Control (S. Tzafestas, Ed.), Plenum, New-York-London (Ch. 7), 1989.

    Google Scholar 

  41. Post, E., “Formal reductions of the general combinatorial problem,” American Journal of Mathe matics, 65, pp. 197–268, 1943.

    Article  MATH  MathSciNet  Google Scholar 

  42. Quilian, M. R., “Semantic memory,” In Minsky (1968), pp. 227–270, 1968.

    Google Scholar 

  43. Quinlan, R., Discovering rules from large collections of examples: A case study. Expert Systems in the Microelectronic Age, Edinburgh, UK: Edinburgh University Press, 1979.

    Google Scholar 

  44. Raiha, K. J., “Bibliography on attribute grammars,” SIGPLAN Notices, 15(5), pp. 35–44, 1980.

    Google Scholar 

  45. Reddy, R., “Epistemology of knowledge based simulation,” Simulation, 48(4), pp. 162–166, 1987.

    Article  Google Scholar 

  46. Reichgelt, H. and van Harmelen, F., “Criteria for choosing representation languages and control regimes for expert systems,” Knowledge Engineering Review, 1(4), pp. 2–17, 1986.

    Article  Google Scholar 

  47. Robinson, J. A., Logic: Form and Function, Edinburgh: Edinburgh University Press, 1979.

    MATH  Google Scholar 

  48. Sassen, J. M. A. and Jaspers, R. B. M., “Design issues of real-time knowledge based systems,” 1992 IFAC/IFIP/IMACS Symp. on AI in Real Time Control, Delft, The Netherlands, 1992.

    Google Scholar 

  49. Shortliffe, E. H., MYCIN: A rule-based computer program for advancing physicians regarding an timicrobial therapy selection, Ph.D. dissertation, Stanford University, (reprinted with revisions as Shortliffe, 1976), 1974.

    Google Scholar 

  50. Shortliffe, E. H., Computer-Based Medical Consultations: MYCIN, New York, American Elsevier, 1976.

    Google Scholar 

  51. Thagard, P., Computational Philosophy of Science, Cambridge, MA: MIT press, 1988.

    Google Scholar 

  52. Touretzy, D. S., Horty, J. F. and Thomason, R. H., “A clash of intuitions: the current state of non monotonic multiple inheritance systems,” Proceedings of the 10th International Joint Conference on Artificial Intelligence, pp. 476–482, 1987.

    Google Scholar 

  53. van Melle, W., A domain-independent system that aids in construting knowledge-based consultation programs, Ph.D. dissertation, Stanford University, 1980.

    Google Scholar 

  54. Woods, E.A., “The hybrid phenomena theory,” Proc. 12th Joint Conf. of AI, (J. Mylopoulos, R. Reiter, Eds), Morgan Kaufmann, 1991.

    Google Scholar 

  55. Woods, E. A. and Balchen, J. G., “Structural estimation with hybrid phenomena theory,” IFAC Workshop on AI in Real Time Control, Sonoma County, California, Sept. 23–25, 1991.

    Google Scholar 

  56. Woods, E., “On representations for continuous dynamic systems,” 1992 IFAC/IFIP/IMACS Symp. on AI in Real-Time Control, Delft, The Netherlands, 1992.

    Google Scholar 

  57. Woods, W., “What’s in a link: foundations for semantic networks,” In Bobrow and Collins (1975), 1975.

    Google Scholar 

Download references

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1993 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Tzafestas, S.G., Kokkinaki, A.I., Valavanis, K.P. (1993). An Overview of Expert Systems. In: Tzafestas, S. (eds) Expert Systems in Engineering Applications. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-84048-7_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-84048-7_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-84050-0

  • Online ISBN: 978-3-642-84048-7

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics