Parallelization of expert systems with recursive applications

Abstract

During the last decade, the number of local area networks (LANs) has increased [1]. LANs provide a path for computers to communicate with each other by sending messages, and by sharing the same databases, programs, expensive memories, and I/O equipment. Parallel programs could also be run on LANs [2]. Expert systems are a subtopic within the artificial intelligence area. A database which is associated with the expert system normally interfaces with it after a question is answered by the end user to find out if any recommendation(s) can be made. A search of the entire list of rules (knowledge base or properly organized database) is then made. A parallel processing application of an expert system with associated database on a LAN was discussed in [3]. It was shown that if the database is seqmented and searched in smaller, but parallel sections, a significant speed-up (computation time on a serial computer/computation time on a parallel computer) can be achieved. In the hierarchically organized knowledge base, intermediate goals may be generated which will lead to the final recommendation. The recursion develops when an intermediate result in one parallel node is needed to make the final recommendation on another parallel node. The knowledge engineer will organize the knowledge base hierarchically, based on the particular rules, goals, and factors. Recursive techniques may be necessary when the knowledge base does not partition easily. In this paper, an algorithm will be developed for expert systems to be run on LANs when resursive applications are needed. The proposed speed-up will be developed using sessions in LANs.