Learning From Demonstrations via Structured Prediction

Charles Parker, Prasad Tadepalli, Weng-Keen Wong, Thomas Dietterich, Alan Fern

Demonstrations from a teacher are invaluable to any student trying to learn a given behavior. Used correctly, demonstrations can speed up both human and machine learning by orders of magnitude. An important question, then, is how best to extract the knowledge encoded by the teacher in these demonstrations. In this paper, we present a method of learning from demonstrations that leverages some of the structured prediction techniques currently under investigation in the literature. We report encouraging results in Wargus, a real-time strategy game.

Subjects: 1.11 Planning; 12. Machine Learning and Discovery

Submitted: May 16, 2007


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