Adaptation is one of the most problematic steps in the design and development of Case Based Reasoning (GBR) 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.
Manzoni, S., Sartori, F., Vizzari, G. (2005). Towards a General Framework for Substitutional Adaptation in Case-Based Reasoning. In S. Bandini, S. Manzoni (a cura di), AI*IA 2005: Advances in Artificial Intelligence 9th Congress of the Italian Association for Artificial Intelligence Milan, Italy, September 21-23, 2005, Proceedings (pp. 331-342). Springer [10.1007/11558590_34].
Towards a General Framework for Substitutional Adaptation in Case-Based Reasoning
Manzoni, SL;Sartori, F;Vizzari, G
2005
Abstract
Adaptation is one of the most problematic steps in the design and development of Case Based Reasoning (GBR) 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.
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