AN OBJECT-ORIENTED KNOWLEDGE-BASE FOR MULTIDOMAIN EXPERT-SYSTEMS

With the current technology of ''deep'' expert systems, domain knowled ge can be modeled, using an object-oriented representation, separately from the strategic knowledge required to make inferences on the domai n. Where such domains involve the construction of some hierarchy or ne twork, a generic inference strategy can be devised to search the domai n knowledge for plausible solutions. Thus, our main concern is in buil ding an appropriate object-class structure that accurately models the problem domain. Rules are merely written to customize the expert syste m according to the uniqueness of each problem domain. Thus, a common f ramework for user interaction can be devised for domains of the same ' 'type.'' By accessing the various domains stored in various knowledge bases, an individual is able to get the benefit of ''expert advice'' a bout several areas, using a somewhat similar interface, varying only a ccording to context and terminology. Hence, the objective of this pape r is to show how deep knowledge can be used to effectively model the d escriptive information of a problem domain without the need to develop and maintain a large rule network. Consequently, we suggest a generic inference strategy that reasons on the deep knowledge via the applica tion of heuristic functions.