Simulation-Assisted Inductive Learning

Bruce G. Buchanan, John Sullivan, Tze-Pin Cheng, Scott H. Clearwater

Learning by induction can require a large number of training examples. We show the power of using a simulator to generate training data and test data in learning rules for an expert system. The induction program is RL, a simplified version of Meta-DENDRAL. The expert system is ABLE, a rule-based system that identifies and locates errors in particle beam lines used in high energy physics. A simulator of beam lines allowed forming and testing rules on sufficient numbers of cases that ABLE’s performance is demonstrably accurate and precise.

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