Augmentation-Based Learning, Combining Observations and User Edits for Programming-by-Demonstration

In this paper we introduce a new approach to Programming-by-Demonstration in which the user is allowed to explicitly edit the procedure model produced by the learning algorithm while demonstrating the task. We describe a new algorithm, Augmentation-Based Learning, that supports this approach by considering both demonstrations and edits as constraints on the hypothesis space, and resolving conflicts in favor of edits.

By: Vittorio Castelli; Daniel Oblinger; Lawrence Bergman

Published in: Knowledge-Based Systems, volume 20, (no 6), pages 575-591 in 2007

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