Response-time optimization of rule-based expert systems

Blaz Zupan; Albert Mo Kim Cheng

doi:10.1117/12.169398

1 March 1994 Response-time optimization of rule-based expert systems

Blaz Zupan, Albert Mo Kim Cheng

Proceedings Volume 2244, Knowledge-Based Artificial Intelligence Systems in Aerospace and Industry; (1994) https://doi.org/10.1117/12.169398
Event: SPIE's International Symposium on Optical Engineering and Photonics in Aerospace Sensing, 1994, Orlando, FL, United States

Abstract

Real-time rule-based decision systems are embedded AI systems and must make critical decisions within stringent timing constraints. In the case where the response time of the rule- based system is not acceptable, it has to be optimized to meet both timing and integrity constraints. This paper describes a novel approach to reduce the response time of rule-based expert systems. Our optimization method is twofold: the first phase constructs the reduced cycle-free finite state transition system corresponding to the input rule-based system, and the second phase further refines the constructed transition system using the simulated annealing approach. The method makes use of rule-base system decomposition, concurrency, and state- equivalency. The new and optimized system is synthesized from the derived transition system. Compared with the original system, the synthesized system has fewer number of rule firings to reach the fixed point, is inherently stable, and has no redundant rules.

Citation Download Citation

Blaz Zupan and Albert Mo Kim Cheng "Response-time optimization of rule-based expert systems", Proc. SPIE 2244, Knowledge-Based Artificial Intelligence Systems in Aerospace and Industry, (1 March 1994); https://doi.org/10.1117/12.169398

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