Case-based reasoning
Adaptation-guided retrieval: questioning the similarity assumption in reasoning
Artificial Intelligence
The Adaption Knowledge Bottleneck: How to Ease it by Learning from Cases
ICCBR '97 Proceedings of the Second International Conference on Case-Based Reasoning Research and Development
Techniques and Knowledge Used for Adaptation During Case-Based Problem Solving
IEA/AIE '98 Proceedings of the 11th International Conference on Industrial and Engineering Applications of Artificial In telligence and Expert Systems: Tasks and Methods in Applied Artificial Intelligence
Using case-base data to learn adaptation knowledge for design
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Soft interchangeability for case adaptation
ICCBR'03 Proceedings of the 5th international conference on Case-based reasoning: Research and Development
Acquiring case adaptation knowledge: a hybrid approach
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Case adaptation by segment replanning for case-based planning systems
ICCBR'05 Proceedings of the 6th international conference on Case-Based Reasoning Research and Development
STATE OF APPLICATIONS IN AI RESEARCHES FROM AI*IA 2005
Applied Artificial Intelligence
Metadata support to retrieve and revise solutions in case-based reasoning
International Journal of Metadata, Semantics and Ontologies
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Adaptation is one of the most problematic steps in the design and development of case-based reasoning (CBR) systems. In fact, it may require considerable domain knowledge and involve complex knowledge engineering tasks, whereas CBR is often adopted when available domain knowledge is not enough to build a problem solution given its description, and thus past experiences are considered and exploited. This paper introduces a general framework for substitutional adaptation, which only requires analogical domain knowledge, which is very similar to the one required to define a similarity function. The approach is formally introduced, and its applicability is discussed with reference to case structure and its variability. A case study focused on the adaptation of cases related to truck tire production processes is also presented.