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Refining the behavior of multiple expert systems: a concept and empirical results

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  • Clyde Holsapple
  • Anita Lee
  • James Otto

Abstract

Expert System Refinement (ESR) is introduced as a means to automatically refine the performance of one or more expert systems. The ESR concept is based on Holland’s learning classifier systems and a method for integrating multiple expert systems. Through users’ feedback about the usefulness/correctness of the integrated expert system’s recommendations, ESR enables behaviors of both individual expert systems as well as the integrated system to improve over time. The ESR concept is tested on a German Credit Database. This empirical evidence suggests that the ESR concept can be usefully applied in automating the process of expert system refinement and multiple expert systems integration. © 1998 John Wiley & Sons, Ltd.

Suggested Citation

  • Clyde Holsapple & Anita Lee & James Otto, 1998. "Refining the behavior of multiple expert systems: a concept and empirical results," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 7(2), pages 81-90, June.
    • Handle: RePEc:wly:isacfm:v:7:y:1998:i:2:p:81-90
    DOI: 10.1002/(SICI)1099-1174(199806)7:23.0.CO;2-7
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