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 author is allowed to explicitly edit the procedure model produced by the learning algorithm while demonstrating the task. We describe Augmentation-Based Learning, a new algorithm that supports this approach by considering both demonstrations and edits as constraints on the hypothesis space, and resolving conflicts in favor of edits. © 2007 Elsevier B.V. All rights reserved.