Title:
Batch versus Interactive Learning by Demonstration

Thumbnail Image
Author(s)
Zang, Peng
Tian, Runhe
Thomaz, Andrea L.
Isbell, Charles L.
Authors
Advisor(s)
Advisor(s)
Editor(s)
Associated Organization(s)
Series
Supplementary to
Abstract
Agents that operate in human environments will need to be able to learn new skills from everyday people. Learning from demonstration (LfD) is a popular paradigm for this. Drawing from our interest in Socially Guided Machine Learning, we explore the impact of interactivity on learning from demonstration. We present findings from a study with human subjects showing people who are able to interact with the learning agent provide better demonstrations (in part) by adapting based on learner performance which results in improved learning performance. We also find that interactivity increases a sense of engagement and may encourage players to participate longer. Our exploration of interactivity sheds light on how best to obtain demonstrations for LfD applications.
Sponsor
This work is supported by the National Science Foundation under Grant No. 0812116.
Date Issued
2010
Extent
Resource Type
Text
Resource Subtype
Post-print
Proceedings
Rights Statement
Rights URI