A desired capability of automatic problem solvers is that they can explain the results. Such explanations should justify that the solution proposed by the problem solver arises fr...
The aim of this paper is to analyze how the generalizations built by a CBR method can be used as local approximations of a concept. From this point of view, these local approximati...
: One of the perceived benefits of Case-Based Reasoning (CBR) is the potential to use retrieved cases to explain predictions. Surprisingly, this aspect of CBR has not been much res...
By design, Case-Based Reasoning (CBR) systems do not need deep general knowledge. In contrast to (rule-based) expert systems, CBR systems can already be used with just some initial...
CBR systems solve problems by assessing their similarity with already solved problems (cases). Explanation of a CBR system prediction usually consists of showing the user the set o...