Case-based reasoning is a methodology with a long tradition in
artificial intelligence that brings together reasoning and machine
learning techniques to solve problems based on past experiences or
cases. Given a problem to be solved, reasoning involves the use of
methods to retrieve similar past cases in order to reuse their
solution for the problem at hand. Once the problem has been solved,
learning methods can be applied to improve the knowledge based on
past experiences. In spite of being a broad methodology applied in
industry and services, case-based reasoning has often been
forgotten in both artificial intelligence and machine learning
books. The aim of this book is to present a concise introduction to
case-based reasoning providing the essential building blocks for
the design of case-based reasoning systems, as well as to bring
together the main research lines in this field to encourage
students to solve current CBR challenges.
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