We describe Augmentation-Based Learning, a new learning algorithm for Programming-by-Demonstration that allows the user to explicitly edit the procedure model even while demonstrating a task. We discuss the problems faced by learning algorithms that support seamless alternation of editing and demonstrations, and show how Augmentation-Based Learning solves them, while at the same time capturing complex procedure models with no additional user intervention.
By: Vittorio Castelli; Daniel Oblinger; Lawrence D. Bergman
Published in: RC23999 in 2006
LIMITED DISTRIBUTION NOTICE:
This Research Report is available. This report has been submitted for publication outside of IBM and will probably be copyrighted if accepted for publication. It has been issued as a Research Report for early dissemination of its contents. In view of the transfer of copyright to the outside publisher, its distribution outside of IBM prior to publication should be limited to peer communications and specific requests. After outside publication, requests should be filled only by reprints or legally obtained copies of the article (e.g., payment of royalties). I have read and understand this notice and am a member of the scientific community outside or inside of IBM seeking a single copy only.
Questions about this service can be mailed to reports@us.ibm.com .