A memory model for an intelligent system for the 21st century

Originally, case-based reasoning emerged from Schank´s theory of dynamic memory. It has then been presented as an artificial intelligence methodology for processing empirical knowledge. Nevertheless, more recent case-based reasoning systems study show how to take advantage from theoretical knowledge to process empirical knowledge more effectively. In order to reach this goal, they propose memory models faithful to the ideal of dynamic memory, for which reasoning and learning are inseparable. The memory model presented here is composed of two parts, an experimental and a theoretical memory expressed in a unified knowledge representation language and organization. The components of the memory are cases and concepts, in the experimental part, and prototypes and models, in the theoretical part. The reasoning supported by this memory model can be various, and takes advantage of all the components, whether experimental or theoretical. It is strongly constrained by some specialized models in theoretical memory, called the points of view