The omnipresence of case-based reasoning in science and application

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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.

论文关键词:Case-based reasoning,Machine learning,Lazy learning

论文评审过程:Received 16 July 1998, Accepted 24 July 1998, Available online 29 December 1998.

论文官网地址:https://doi.org/10.1016/S0950-7051(98)00066-5