Performance evaluation of rule grouping on a real-time expert system architecture

Uses a Markov process to model a real-time expert system architecture characterized by message passing and event-driven scheduling. The model is applied to the performance evaluation of rule grouping for real-time expert systems running on this architecture. An optimizing algorithm based on Kernighan-Lin heuristic graph partitioning for the real-time architecture is developed and a demonstration system based on the model and algorithm has been developed and tested on a portion of the advanced GPS receiver (AGR) and manned manoeuvring unit (MMU) knowledge bases.<
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