Overview of the Prodigy Learning Apprentice
This paper briefly describes the PRODIGY system1, a learning apprentice for robot construction tasks currently being developed at Carnegie-Mellon University. After solving a problem, PRODIGY re-examines the search tree and analyzes its mistakes. By doing so, PRODIGY can often find efficient tests for determining if a problem solving method is applicable. If adequate performance cannot be achieved through analysis alone, PRODIGY can initiate a focused dialogue with a teacher to learn the circumstances under which a problem solving method is appropriate.
KeywordsSearch Tree Inference Rule Paper Briefly Solution Sequence Applicability Condition
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