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ABSTRACT
<p>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.</p>
INDEX TERMS
software performance evaluation; message passing; expert systems; real-time systems; Markov processes; scheduling; optimisation; heuristic programming; graph theory; Global Positioning System; receivers; man-machine systems; telecommunication computing; aerospace computing; performance evaluation; rule grouping; real-time expert system architecture; Markov process; message passing; event-driven scheduling; optimizing algorithm; Kernighan-Lin heuristic graph partitioning; advanced GPS receiver; Global Positioning System; manned manoeuvring unit; knowledge bases
CITATION
I.-R. Chen, B. Poole, "Performance Evaluation of Rule Grouping on a Real-Time Expert System Architecture", IEEE Transactions on Knowledge & Data Engineering, vol. 6, no. , pp. 883-891, December 1994, doi:10.1109/69.334879
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