Case-Based Approximate Reasoning

Making use of different frameworks of approximate reasoning and reasoning under uncertainty, notably probabilistic and fuzzy set-based techniques, this book develops formal models of the above inference principle, which is fundamental to CBR. The case-based approximate reasoning methods thus obtained especially emphasize the heuristic nature of case-based inference and aspects of uncertainty in CBR.

From the reviews:

"In the last years developments were very successful that have been based on the general concept of case-based reasoning. ... will get a lot of attention and for a good while will be the reference for many applications and further research. ... the book can be used as an excellent guideline for the implementation of problem-solving programs, but also for courses in Artificial and Computional Intelligence. Everybody who is involved in research, development and teaching in Artificial Intelligence will get something out of it." (Christian Posthoff, Zentralblatt MATH, Vol. 1119 (21), 2007)