A model and its different applications to case-based reasoning

摘要

A model to implement the case-based reasoning developed from using a neural net as a base to calculate a measure of similarity between the new problem and each case is presented. It is shown how the neural net provides a mechanism to retrieve cases considering information that in other models needs a parallel architecture. Moreover, in this paper it is analyzed how the model can be employed to create expert networks and case-based planners.