A machine learning method for multi-expert decision support

Clyde Holsapple, Anita Lee and Jim Otto

Annals of Operations Research, 1997, vol. 75, issue 0, 188 pages

Abstract: When a decision maker has access to multiple expert systems, each embodying a different expert perspective on analyzing and reasoning about the same kind of decision problem, an important consideration is which to use at what times. We address this issue with a method based on competition among the distinct expert systems (and their respective rules). We begin by reviewing prior research concerned with the coordination of multiple sources of expertise in support of decision making, pointing out potential weaknesses of the proposed methods. Next, we introduce a new coordination method based on the competitive paradigm that has been applied in machine learning. This method involves adjustments to the strengths of expert systems and to their constituent rules based on their performances. A nine-step process for adjusting strengths is described. Advantages and limitations of this new method for expert system coordination are discussed. We outline an approach to testing the coordination method and report on preliminary testing of the performance of a system employing our method versus the performance of individual experts. Copyright Kluwer Academic Publishers 1997

Date: 1997
References: Add references at CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://hdl.handle.net/10.1023/A:1018955328719 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:annopr:v:75:y:1997:i:0:p:171-188:10.1023/a:1018955328719

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

DOI: 10.1023/A:1018955328719

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().