Performance Evaluation of Rule Grouping on a Real-Time Expert System Architecture

  • Authors:
  • I. -R. Chen;B. Poole

  • Affiliations:
  • -;-

  • Venue:
  • IEEE Transactions on Knowledge and Data Engineering
  • Year:
  • 1994

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Abstract

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.