A review on fundamentals of case-based reasoning and its recent application in different domains

Abstract

Case-based reasoning (CBR) means to understand and solve new (target) problems using past experiences. It solves target problems based on the solutions of similar past problems or by adapting solutions of past problems. It is a new branch of artificial intelligence (AI) approach to problem solving and learning that has attained huge attention over the last few years. This paper brings current state-of-art of working principle as well as its application domains with much other advancement together, which is really very rare in a single research article. This research article starts with about CBR and its basic working principle. The article states a brief-history of CBR, walks around its applications for a newly interested CBR reader or researcher, describes the methods involved in CBR with brief explanation and discusses the merits of CBR methodology and their differences from other related techniques and methodologies. Besides, the article digs out the prominent and essential further potential research challenges and issues in CBR. It also reports about the use of CBR as an integrated approach of reasoning and learning with other learning methods and makes critical assessment together with suggestion for further improvement.