An adaptive agent for case description in diagnostic CBR systems

被引:15
作者
Montazemi, AR
Gupta, KM
机构
[1] School of Business, McMaster University, Hamilton
基金
加拿大自然科学与工程研究理事会;
关键词
case based reasoning; diagnostic systems; adaptive agents; decision support systems; information filtering;
D O I
10.1016/0166-3615(96)00006-1
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Case-based reasoning (CBR) systems can support diagnosis of complex industrial systems. The success of a diagnostic CBR system depends on its ability to retrieve previous cases that provide information to solve a new case. To this end, the new case must be adequately described. However, to describe a new case in an ill-structured diagnostic decision environment requires considerable domain knowledge and is dependent on the strategies used by a decision maker. In this paper, we develop a framework for the development of an adaptive agent that can assist a decision maker describe a new case to a diagnostic CBR system. The adaptive agent is dynamic and provides its recommendations based on the diagnostic strategy of a decision maker. An empirical evaluation of the proposed framework in the diagnostic of complex industrial machinery supports its effectiveness.
引用
收藏
页码:209 / 224
页数:16
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