Artificial intelligence in engineering design (Volume I): design representation and models of routine design
Case-based reasoning
Case-Based Reasoning in Design
Case-Based Reasoning in Design
A Similarity Metric for Retrieval of Cases Imperfectly Explained
EWCBR '93 Selected papers from the First European Workshop on Topics in Case-Based Reasoning
Reasoning with Cases Imperfectly Described and Explained
EWCBR '94 Selected papers from the Second European Workshop on Advances in Case-Based Reasoning
A data mining-based engineering design support system: a research agenda
Data mining for design and manufacturing
Solution verification in software design: a CBR approach
ICCBR'03 Proceedings of the 5th international conference on Case-based reasoning: Research and Development
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Learning is an intrinsic product of case-based reasoning. Acquiring new cases is one possible way of learning in a case-based system. These cases comprise mainly success knowledge. The successful cases are essentially used to generate new design solutions. But a case-based system also can make use of failure knowledge. In this paper we present how a case-based system can acquire failure cases for verification of the solution created by success cases. We describe IM-RECIDE, a system that uses case-based reasoning for solving design problems that are imperfectly described and explained. The learning aspect is focused and some of the machine learning dimensions in design are criticized. Experimental results in the domain of room configuration also are presented.