Demonstration of PLOW: a dialogue system for one-shot task learning

Authors:
James Allen;Nathanael Chambers;George Ferguson;Lucian Galescu;Hyuckchul Jung;Mary Swift;William Taysom
Affiliations:
Florida Institute for Human and Machine Cognition, Pensacola, FL;Florida Institute for Human and Machine Cognition, Pensacola, FL;University of Rochester, Rochester, NY;Florida Institute for Human and Machine Cognition, Pensacola, FL;Florida Institute for Human and Machine Cognition, Pensacola, FL;University of Rochester, Rochester, NY;Florida Institute for Human and Machine Cognition, Pensacola, FL
Venue:
NAACL-Demonstrations '07 Proceedings of Human Language Technologies: The Annual Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations
Year:
2007

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Abstract

We describe a system that can learn new procedure models effectively from one demonstration by the user. Previous work to learn tasks through observing a demonstration (e.g., Lent & Laird, 2001) has required observing many examples of the same task. One-shot learning of tasks presents a significant challenge because the observed sequence is inherently incomplete -- the user only performs the steps required for the current situation. Furthermore, their decision-making processes, which reflect the control structures in the procedure, are not revealed.