Towards a general framework for substitutional adaptation in case-based reasoning

Authors:
Sara Manzoni;Fabio Sartori;Giuseppe Vizzari
Affiliations:
Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milan, Italy;Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milan, Italy;Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milan, Italy
Venue:
AI*IA'05 Proceedings of the 9th conference on Advances in Artificial Intelligence
Year:
2005

Citing 11
Cited 0

Case-based reasoning

Case-based reasoning
Adaptation-guided retrieval: questioning the similarity assumption in reasoning

Artificial Intelligence
An Adaptation Heuristic for Case-Based Estimation

EWCBR '98 Proceedings of the 4th European Workshop on Advances in Case-Based Reasoning
Structured Cases, Trees and Efficient Retrieval

EWCBR '98 Proceedings of the 4th European Workshop on Advances in Case-Based Reasoning
Similarity Measures for Object-Oriented Case Representations

EWCBR '98 Proceedings of the 4th European Workshop on Advances in Case-Based Reasoning
Towards a Unified Theory of Adaption in Case-Based Reasoning

ICCBR '99 Proceedings of the Third International Conference on Case-Based Reasoning and Development
CBR Adaptation for Chemical Formulation

ICCBR '01 Proceedings of the 4th International Conference on Case-Based Reasoning: Case-Based Reasoning Research 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
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
Acquiring case adaptation knowledge: a hybrid approach

AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1

Quantified Score

Hi-index	0.00

Visualization

Abstract

Adaptation is one of the most problematic steps in the design and development of Case Based Reasoning (CBR) systems, as it may require considerable domain knowledge and involve complex knowledge engineering tasks. This paper describes a general framework for substitutional adaptation, which only requires analogical domain knowledge, very similar to the one required to define a similarity function. The approach is formally defined, 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 tyre production processes is also presented.