Explaining and repairing plans that fail
Artificial Intelligence
De´ja` Vu: a hierarchical case-based reasoning system for software design
ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
Case-Based Learning: Beyond Classification of Feature Vectors
ECML '97 Proceedings of the 9th European Conference on Machine Learning
An Adaptation Heuristic for Case-Based Estimation
EWCBR '98 Proceedings of the 4th European Workshop on Advances in Case-Based Reasoning
Case-Based Design for Tablet Formulation
EWCBR '98 Proceedings of the 4th European Workshop on Advances in Case-Based Reasoning
Genetic Algorithms to Optimise CBR Retrieval
EWCBR '00 Proceedings of the 5th European Workshop on Advances in Case-Based Reasoning
Applying Recursive CBR for the Custumization of Structured Products in an Electronic Shop
EWCBR '00 Proceedings of the 5th European Workshop on Advances in Case-Based Reasoning
A Support System Based on CBR for the Design of Rubber Compounds in Motor Racing
EWCBR '00 Proceedings of the 5th European Workshop on Advances in Case-Based Reasoning
Building Compact Competent Case-Bases
ICCBR '99 Proceedings of the Third International Conference on Case-Based Reasoning and Development
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
Refining Conversational Case Libraries
ICCBR '97 Proceedings of the Second International Conference on Case-Based Reasoning Research and Development
Using case-base data to learn adaptation knowledge for design
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Acquiring case adaptation knowledge: a hybrid approach
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
An Application of Case-Based Reasoning to the Adaptive Management of Wireless Networks
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
Mining Large-Scale Knowledge Sources for Case Adaptation Knowledge
ICCBR '07 Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Using Case Provenance to Propagate Feedback to Cases and Adaptations
ECCBR '08 Proceedings of the 9th European conference on Advances in Case-Based Reasoning
Knowledge Planning and Learned Personalization for Web-Based Case Adaptation
ECCBR '08 Proceedings of the 9th European conference on Advances in Case-Based Reasoning
Case-Based student modeling in multi-agent learning environment
CEEMAS'05 Proceedings of the 4th international Central and Eastern European conference on Multi-Agent Systems and Applications
A general introspective reasoning approach to web search for case adaptation
ICCBR'10 Proceedings of the 18th international conference on Case-Based Reasoning Research and Development
Enhancing case adaptation with introspective reasoning and web mining
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Metadata support to retrieve and revise solutions in case-based reasoning
International Journal of Metadata, Semantics and Ontologies
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Adaptation is an important step in CBR when applied to design tasks. However adaptation knowledge can be difficult to acquire directly from an expert. Nevertheless, CBR tools provide few facilities to assist with the acquisition of adaptation knowledge. This paper considers a special class of design task, where a component-based solution can be developed in stages, and suggests adaptation knowledge that is suited to CBR systems for component-based design. A case-based adaptation is proposed where the adaptation cases are generated from the original problem-solving case-base, and so knowledge acquisition is automated. Both numeric and nominal targets are adapted, although a different case-based adaptation is applied for each. The gains of adaptation are presented for a tablet formulation application, although the approach is suited for other formulation and configuration tasks that apply a component-based approach to design. The learned adaptation knowledge is understandable to the expert, with the effect that he can criticise the content and refine the knowledge if necessary. Results are promising but the case-based adaptation systems offer many opportunities for optimisation and further learning.