Basic CBR Elements

The chapter presents the basic notions used in CBR and necessary for understanding the remainder of this book. Case-based reasoning is a reasoning methodology for problem solving. It mainly relies on experiences in which problems were solved in the past. CBR reuses previous experiences to solve current, new problems. Problem solving experiences include problems and solutions. CBR can be used to perform multiple reasoning tasks, such as classification, planning, and design. Problems are submitted to a CBR system through what we call query problems. Once a new query problem is formulated through the set of attributes defined for case representation, similar cases can be retrieved. Case retrieval utilizes a similarity measure to search for similar cases whose solutions may be reused to solve the new query problem. How to assess similarity between cases is a core method in CBR. The problem in the retrieved case is typically very similar to, but not exactly the same as the query problem. This may cause the solution in the retrieved case not to be perfectly suitable for solving the new query problem. Adaptation is the step that modifies the solution in the retrieved case in order to make it perfectly suitable for solving the query problem. There are two models of CBR. The CBR process model incorporates formulating the problem, retrieving solutions, reusing them, revising and repairing them, and storing them as new experiences. The CBR knowledge model describes the containers where knowledge is stored. There are four knowledge containers: Vocabulary, Case Base, Similarity, and Adaptation. From reading this chapter, the reader has a deeper understanding of the CBR process.