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Publication Details

Iteration Learning by Demonstration

by Eker, S. and Lee, T. J. and Gervasio, M.

in Papers from the AAAI 2009 Spring Symposium on Agents that Learn from Human Teachers

2009.

Abstract

Programming by demonstration (PBD) utilizes a human teacher to train a computer system to perform tasks within that system. This technique effectively improves productivity for many tasks, in many domains. Many tasks are repetitive in nature; these can be learned by PBD by recognizing the repetitions and generalizing these to iterative programs. We present a domain-independent approach to iteration learning by demonstration based on a dataflow model of user actions. We discuss alternatives to our approach and their tradeoffs. In doing so, we identify criteria useful for characterizing iteration learning by demonstration.

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Associated Projects

CALO

Cognitive Assistant that Learns and Organizes

As part of DARPA’s Personalized Assistant that Learns (PAL) program, SRI and team members are working on developing a next-generation "Cognitive Agent that Learns and Organizes" (CALO).

AIC Personnel

Name Title E-mail
Gervasio, Melinda Senior Computer Scientist
Lee, Thomas (Tom) J Senior Research Engineer

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