A numerical strategy to defectuous knowledge using

Knowledge-Based Systems are based on an often defectuous knowledge, be this knowledge acquired from experts or learned from examples. This paper presents a strategy designed to cope with defectuous knowledge: given a set of rules, it builds a similarity function over the work space of the problem. This similarity function together with a set of examples then enables case-based reasoning, through a K-nearest-neighbour-like process. Compared to other case-based reasoning techniques, the advantage of this approach is the following: the ‘topology’ of the space is automatically induced from the given rules, instead of being explicitly provided (and tuned) by the expert.