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Proceedings Paper

Response-time optimization of rule-based expert systems
Author(s): Blaz Zupan; Albert Mo Kim Cheng
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Paper 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.

Paper Details

Date Published: 1 March 1994
PDF: 9 pages
Proc. SPIE 2244, Knowledge-Based Artificial Intelligence Systems in Aerospace and Industry, (1 March 1994); doi: 10.1117/12.169398
Show Author Affiliations
Blaz Zupan, Univ. of Houston (United States)
Albert Mo Kim Cheng, Univ. of Houston (United States)

Published in SPIE Proceedings Vol. 2244:
Knowledge-Based Artificial Intelligence Systems in Aerospace and Industry
Wray Buntine; Doug H. Fisher, Editor(s)

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