Consensus Knowledge Acquisition 1

We have developed a method and prototype program, called carter, that assists two experts in agreeing on what knowledge should go into a single, consensus knowledge base, i.e., a knowledge base that reeects the best judgment of each of them. We show that consensus building can be eeectively facilitated by a debugging approach that identiies, explains, and resolves diierences in the knowledge of the two experts. carter's expertise is in the task of consensus building; its knowledge base is a collection of some 35 entries, each made up of a discrepancy detection procedure and a corresponding resolution procedure. Examples of the use of this knowledge are illustrated with descriptions of the program in operation, assisting with the reconciliation of two independently developed knowledge based systems. A signiicant part the program's task lies in nding the places where the two knowledge bases match (e.g., two concepts that may be labeled diierently but actually mean the same thing), where they diier, and where they overlap. The program displays an interesting degree of success in using circumstantial evidence in the knowledge bases themselves to help infer the degree of overlap in the intended meaning of concepts. We also show that the same fundamental technique is necessary for matching any two independently constructed representations, and that the richer the set of primitives provided by the representation in use, the more conndence we can place in the circumstantial evidence that is available.