Machine learning algorithins have application potential in simulation at stages of model building, simulation execution monitoring in real-time, and output analysis and model refinement. This article presents the basics of the inductive learning paradigm and the ID3 algorithm, highlights the potential of learning in simulation as means for extracting heuristic rules to be used in expert systems, and demonstrates a sample application in simulation of queuing systems.
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