Abstract Inference Structures to Support Variable Rule Structures for Expert Systems

Knowledge‐based systems have been successfully utilised in the develop‐ment of complex systems. In many cases, these systems have emphasised the need for techniques to integrate knowledge‐based processing with methods for managing both large amounts of data and knowledge. However, many potential applications for expert systems are precluded by limitations in the ability of conventional expert system technology to function in conjunction with data systems without manual intervention. The author focuses on the integration of knowledge‐bases and databases with the capability to: store and context select between parallel, competing expert system rule structures; cascade variable rule structures; allow an expert system to be interrupted and to be subsequently restarted by storing the state of the inference engine; handle simple data storage and retrieval.