The omnipresence of case-based reasoning in science and application

被引：92

作者：

Aha, DW ^{[1
]}

机构：

[1] USN, Res Lab, Navy Ctr Appl Res Artificial Intelligence, Washington, DC 20375 USA

来源：

KNOWLEDGE-BASED SYSTEMS | 1998年 / 11卷 / 5-6期

关键词：

case-based reasoning; machine learning; lazy learning;

D O I：

10.1016/S0950-7051(98)00066-5

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A surprisingly large number of research disciplines have contributed towards the development of knowledge on lazy problem solving, which is characterized by its storage of ground cases and its demand-driven response to queries. Case-based reasoning (CBR) is an alternative, increasingly popular approach for designing expert systems that implements this approach. This paper lists pointers to some contributions in some related disciplines that offer insights for CBR research. We then outline a small number of Navy applications based on this approach that demonstrate its breadth of applicability. Finally, we list a few successful and failed attempts to apply CBR, and list some predictions on the future roles of CBR in applications. Published by Elsevier Science B.V.

引用

页码：261 / 273

页数：13