|Publication Type||Conference Paper|
|Year of Publication||2001|
|Authors||de Mántaras RLópez|
|Editor||Paliouras G., Karkaletsis V., Spyropoulos C.D|
|Conference Name||Lecture Notes in Artificial Intelligence|
This chapter contains an overview of Case-Based Reasoning (CBR). The main goal is to have a balance between brevity and expressiveness and to provide helpful pointers to literature in the field. To do so, we first describe the CBR types and the CBR cycle, then we briefly review a representative set of systems, next we discuss the connections between CBR and learning. The main part of the chapter analyses the most important issues and problems of the CBR components, such as indexing/retrieval/selection, memory organization, adaptation/evaluation, forgetting and integration with other techniques. Finally, we discuss the added value of incorporating fuzzy techniques in CBR and briefly describe some representative Fuzzy-CBR systems.
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