Integrating case-based and rule based reasoning: the possibilistic connection

Rule based reasoning (RBR) and case based reasoning (CBR) have emerged as two impor­ tant and complementary reasoning methodolo­ gies in artificial intelligence (AI). For problem solving in complex, real world situations, it is useful to integrate RBR and CBR. This paper presents an approach to achieve a compact and seamless integration of RBR and CBR within the base architecture of rules. The paper fo­ cuses on the possibilistic nature of the approx­ imate reasoning methodology common to both CBR and RBR. In CBR, the concept of simi­ larity is casted as the complement of the dis­ tance between cases. In RBR the transitivity of similarity is the basis for the approximate deductions based on the generalized modus po­ nens. It is shown that the integration of CBR and RBR is possible without altering the in­ ference engine of RBR. This integration is illustrated in the financial domain of mergers and acquisitions. These ideas have been implemented in a prototype system, called MARS.