Automatic knowledge learning and case adaptation with a hybrid committee approach

When Case Based Reasoning systems are applied to real-world problems, the retrieved solutions usually require adaptations in order to be used on new contexts. Therefore, case adaptation is a desirable capability. However, case adaptation is still a challenge for this research area. In general, the acquisition of knowledge for case adaptation is harder than the acquisition of cases. This paper explores the automatic learning of adaptation knowledge and explores the use of a hybrid committee approach for automatic case adaptation.