Our learning diagnostic skills (LDS) system compiles an efficient diagnostic model for each power supply circuit presented to it. The inputs are individual schematics and a shared general causal model of power-supply failures. Because the general model is reused for each power supply design, knowledge acquisition for a new power supply is limited to adding diagnostic schema not already covered by the general model and providing an annotated circuit schematic. We have used an existing technique, partial evaluation (PE), to produce efficient diagnosis of power supplies. The use of PE compensates for the computational costs caused by the expressiveness and generality of the shared knowledge representation we use and therefore eases further the knowledge acquisition bottleneck in expert system development. Using PE, our system takes general knowledge, written in a highly expressive language, and automatically compiles the complete knowledge base for an efficient expert system diagnostician for each specific device.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Leonard Friedman, Leonard Friedman, } "Automatic compilation of expert systems", Proc. SPIE 1963, Applications of Artificial Intelligence 1993: Knowledge-Based Systems in Aerospace and Industry, (23 March 1993); doi: 10.1117/12.141738; https://doi.org/10.1117/12.141738


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