• Rajiv Khosla
  • Ishwar K. Sethi
  • Ernesto Damiani
Part of the The Springer International Series in Engineering and Computer Science book series (SECS, volume 582)


The applications in this book employ a number of technologies. These technologies can be grouped under intelligent systems, software engineering, agents, multimedia and the internet/electronic commerce. This chapter introduces the reader to these technologies. The various technologies covered in this chapter are:
  • Expert Systems

  • Case based Reasoning

  • Artificial Neural Networks

  • Fuzzy Systems

  • Genetic Algorithms

  • Intelligent Fusion, Transformation and Combination

  • Object-Oriented Technology

  • Agents and Agent Architectures

  • Multimedia

  • XML — the new internet standard


Genetic Algorithm Expert System Fuzzy System Fuzzy Rule Agent Architecture 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Adler S. (1998), “Initial Proposal for XSL”, available from:
  2. Aitkins, J. (1983), “Prototypical Knowledge for Expert Systems,” Artificial Intelligence, vol. 20, pp. 163–210.CrossRefGoogle Scholar
  3. Balzer, R., Erman, L. D., London, P. E. and Williams, C. (1980), “Hearsay-III:A Domain-Independent Framework for Expert Systems,” in First National Conference on Artificial Intelligence (AAAI), pp. 108–110Google Scholar
  4. Berry, J. T. (1988), C++ Programming, Howard W. Sams and company, Indianapolis, Indiana, USA.Google Scholar
  5. Blair B. and Boyer J. (1999), “XFDL: Creating Electronic Commerce Transaction Records Using XML”, Proceedings of the WWW8 Intl. Conference, Toronto, Canada, pp. 533–544Google Scholar
  6. Bray T. et al. (ed.) (1998), “Extensible Markup Language (XML) 1.0”, available at
  7. Encyclopedia Britanica, (1986), Articles on “Behaviour, Animal,” “Classification Theory,” and “Mood,” Encyclopedia Britanica, Inc.Google Scholar
  8. Chandrasekaran, B. (1990), What Kind of Information Processing is Intelligence, TheGoogle Scholar
  9. Foundations of AI: A Sourcebook, Cambridge, UK: Cambridge University Press, pp. 14–46.Google Scholar
  10. Coad, P. and Yourdon, E. (1990), Object-Oriented Analysis, Prentice Hall, Englewood Cliffs, NJ, USA.Google Scholar
  11. Coad, P. and Yourdon, E. (1991), Object-Oriented Analysis and Design, Prentice Hall, Englewood Cliffs, NJ, USA.Google Scholar
  12. Coad, P. and Yourdon, E. (1992), Object-Oriented Design, Prentice Hall, Englewood Cliffs, NJ, USA.Google Scholar
  13. Cox, B. J. (1986), Object-Oriented Programming,Addison-Wesley.Google Scholar
  14. Dillon, T. and Tan, P. L. (1993), Object-Oriented Conceptual Modeling, Prentice Hall, Sydney, Australia.Google Scholar
  15. Erman, L. D., Hayes-Roth, F., Lesser, V. R. and Reddy, D. R. (1980), “The Hearsay-II Speech-Understanding System: Integrating Knowledge to Resolve Uncertainty, “ ACM Computing Surveys,vol. 12, no. 2, June, pp. 213–53.Google Scholar
  16. Erman, L. D., London, P. E. and Fickas, S. F. (1981), “The Design and an Example Use of Hearsay-III,” in Seventh International Joint Conference on Artificial Intelligence, pp. 409–15.Google Scholar
  17. Finin T., Fritzson R., MacKay D. and MacEntire R. (1994), “KQML as an Agent Communication Language, Proceedings of the Third International Conference on Information and Knowledge Management,pp.112–124Google Scholar
  18. Greffenstette, J.J. (1990) “Genetic Algorithms and their Applications” Encyclopedia of Computer Science and Technology, vol. 21, eds. A. Kent and J. G. William, AIC-90–006, Navla Research laboratory, Washington DC, pp. 139–52.Google Scholar
  19. Goldberg, D.E. (1989), Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley, Reading, MA, pp. 217–307.zbMATHGoogle Scholar
  20. Hamscher, W. (1990), “XDE: Diagnosing Devices with Hierarchic Structure and Known Failure Modes,” Sixth Conference of Artificial Intelligence Applications, California, pp. 48–54.CrossRefGoogle Scholar
  21. Hawryszkiewyz, I. T. (1991), Introduction to System Analysis and Design, Prentice Hall, Sydney, Australia.Google Scholar
  22. Hayes-Roth, F., Waterman, D. A. and Lenat, D. B. (1983), Building Expert Systems, Addison-Wesley.Google Scholar
  23. Haykin, 1994 Neural Networks: A comprehensive foundation. IEEE Press, New York.zbMATHGoogle Scholar
  24. Hebb, D. (1949), The Organisation of Behaviour, Wiley, New York.Google Scholar
  25. Holland, J. (1975), Adaptation in Neural and Artificial Systems, University of Michigan Press, Ann Arbor, Michigan, USA.Google Scholar
  26. Inmon, W.H., and Kelley, C., (1993), RdbNMS, Developing the Data Warehouse, QED, Publication Group, Boston, USA.Google Scholar
  27. Kim, Ballou, Chou, Garza and Woelk (1988), “Integrating an Object-Oriented Programming System with a Database System,” ACM OOPSLA Proceedings, October.Google Scholar
  28. Kohonen, T. (1990), Self Organisation and Associative Memory, Springer-Verlag.Google Scholar
  29. Kolodner, J. L. (1984), “Towards an Understanding of the Role of Experience in the Evolution from Novice to Expert,” Developments in Expert Systems, London: Academic Press.Google Scholar
  30. Kraft, A. (1984), “XCON: An Expert Configuration System at Digital Equipment Corporation,” The Al Business: Commercial Uses of Artificial Intelligence, Cambridge, MA: MIT Press.Google Scholar
  31. McClelland, J. L., Rumelhart, D. E. and Hinton, G.E. (1986), “The Appeal of Parallel Distributed Processing,” Parallel Distributed Processing, vol. 1, Cambridge, MA: The MIT Press, pp. 3–40Google Scholar
  32. Minsky, M. and Papert, S. (1969), Perceptrons,MIT press.Google Scholar
  33. Minsky, M. (1981) “A Framework for representing Knowledge,” Mind Design, Cambridge, MA: the MIT Press, pp. 95–128.Google Scholar
  34. Myer, B. (1988), Object-Oriented Software Construction, Prentice Hall.Google Scholar
  35. Neibur, D. and Germond, A. J. (1992) “Power System Static Security Assessment Using The Kohonen Neural Network Classifier,” IEEE Transactions on Power Systems, May, vol. 7, no. 2, pp. 865–72.Google Scholar
  36. Newell, A. (1977), “On Analysis of Human Problem solving,” Thinking: Readings in Cognitive Science, Cambridge UK: Cambridge University Press.Google Scholar
  37. Ng, H.T., 1991, “Model-Based, Multiple-Fault Diagnosis of Dynamic, Continuous Physical Devices,” IEEE Expert, pp. 38–43.Google Scholar
  38. Pardi W. J. (1999), XML In Action, Microsoft PressGoogle Scholar
  39. Pressman, R. S. (1992), Software Engineering: A Practioner’s Approach, McGraw Hill International, Singapore.Google Scholar
  40. Quillian, M. R. (1968), “Semantic Memory,” Semantic Information Processing, Cambridge, MA: The MIT Press, pp. 227–270.Google Scholar
  41. Rumbaugh, J. et al. (1990), Object-Oriented Modeling and Design, PrenticeHall, Englewood Cliffs, NJ, USA.Google Scholar
  42. Rumelhart, D. E., Hinton, G. E. and Williams, R. J. (1986), “Learning Internal Representations by Error Propagation,” Parallel Distributed Processing, vol. 1, Cambridge, MA: The MIT Press, pp. 318–362.Google Scholar
  43. Russell, S., and Norvig, P. (1995), Artificial Intelligence–A Modern Approach, Prentice Hall, New Jersey, USA, pp. 788–790.zbMATHGoogle Scholar
  44. Schank, R. C. (1972), “Conceptual Dependency,” Cognitive Psychology, vol. 3,pp. 552–631.CrossRefGoogle Scholar
  45. Schank, R. C. and Abelson, R. P. (1977), Scripts, Plans, Goals and Understanding, Hillsdale, NJ: Lawerence Erlbaum. 42zbMATHGoogle Scholar
  46. Sejnowski, T.J., and Rosenberg, C.R. (1987), “Parallel Networks that Learn to Pronounce English Text,” Complex Systems, pp, 145–168.Google Scholar
  47. Shortliffe, E.H. (1976), Computer-based Medical Consultation: MYCIN, New York: American Elsevier.Google Scholar
  48. Smolensky, P. (1990), “connectionism and Foundations of AI”, The Foundations of AI: A Sourcebook, Cambridge, UK: Cambridge University.Google Scholar
  49. Steels, L. (1989), “Artificial Intelligence and Complex Dynamics,” Concepts and Characteristics of Knowledge Based Systems, Eds., M. Tokoro, et al., North Holland, pp. 369–404.Google Scholar
  50. Unland, R, and Schlageter, G. (1989), “An Object-Oriented Programming Environment for Advanced Database Applications,” Journal of Object-Oriented Programming, May/June.Google Scholar
  51. Wang, X. and Dillon, T. S. (1992), “A Second Generation Expert System for Fault Diagnosis,” in Journal of Electrical Power and Energy Systems, April/June, 14 (2/3), pp. 212–16.Google Scholar
  52. Widrow, B., and Hoff, M.E. (1960), “Adaptive Switching Circuits,” IRE WESCON Convention Record, Part 4, pp. 96–104.Google Scholar
  53. World Wide Web Consortium (1998), “Extensible Markup Language (XML) 1.0” (W3C Recommendation )
  54. World Wide Web Consortium (1999), “Namespaces in XML” (W3C Recommendation )
  55. Zadeh, L.A. (1965), “Fuzzy sets,” Information and Control, vol. 8, pp. 338–353.MathSciNetzbMATHCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2000

Authors and Affiliations

  • Rajiv Khosla
  • Ishwar K. Sethi
  • Ernesto Damiani

There are no affiliations available

Personalised recommendations