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Knowledge-Based Systems and the Decision Sciences

Author

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  • Barry G. Silverman

    (Institute for Artificial Intelligence, George Washington University, Staughton Hall, Room 206, Washington, DC 20052)

Abstract

Three ways of unifying knowledge-based expert systems and mathematical modeling are (1) knowledge-based decision aids that support the steps of the decision cycle unaddressed by mathematics; (2) intelligent decision modeling systems that help users build, apply, and manage libraries of models; and (3) decision analytic expert systems that integrate theoretically rigorous methods of uncertainty into the expert system knowledge bases. Many contributions have been made to these three types of unification over the past half decade, and working examples of each are now proliferating. Both the applied mathematical sciences and knowledge-based systems are richer fields as a result of this synthesis. More work remains to be done.

Suggested Citation

  • Barry G. Silverman, 1995. "Knowledge-Based Systems and the Decision Sciences," Interfaces, INFORMS, vol. 25(6), pages 67-82, December.
    • Handle: RePEc:inm:orinte:v:25:y:1995:i:6:p:67-82
    DOI: 10.1287/inte.25.6.67
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    Cited by:

    1. Davis, Jefferson T. & Massey, Anne P. & Lovell, Ronald E. R., 1997. "Supporting a complex audit judgment task: An expert network approach," European Journal of Operational Research, Elsevier, vol. 103(2), pages 350-372, December.

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