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Training a Robot via Human Feedback: A Case Study.
W. Bradley Knox, Peter
Stone, and Cynthia Breazeal.
In International Conference on
Social Robotics, October 2013.
BEST PAPER AWARD WINNER at ICSR 2013
An
associated video summarizing the paper (direct
link).
We present a case study of applying a framework for learning from numeric human feedback---TAMER---to a physically embodied robot. In doing so, we also provide the first demonstration of the ability to train multiple behaviors by such feedback without algorithmic modifications and of a robot learning from free-form human-generated feedback without any further guidance or evaluative feedback. We describe transparency challenges specific to a physically embodied robot learning from human feedback and adjustments that address these challenges.
@InProceedings{ICSR13-knox,
author = {W. Bradley Knox and Peter Stone and Cynthia Breazeal},
title = {Training a Robot via Human Feedback: A Case Study},
booktitle = {International Conference on Social Robotics},
location = {Bristol, UK},
month = {October},
year = {2013},
abstract = {We present a case study of applying a framework for learning from numeric human feedback---TAMER---to a physically embodied robot. In doing so, we also provide the first demonstration of the ability to train multiple behaviors by such feedback without algorithmic modifications and of a robot learning from free-form human-generated feedback without any further guidance or evaluative feedback. We describe transparency challenges specific to a physically embodied robot learning from human feedback and adjustments that address these challenges.
},
wwwnote={<b>BEST PAPER AWARD WINNER</b> at <a href="http://www.icsr2013.org.uk">ICSR 2013</a><br>An associated <a href="http://labcast.media.mit.edu/?p=300">video summarizing the paper</a> (<a href="http://www.cs.utexas.edu/~pstone/Movies/TAMER.mov">direct link</a>).
}
}
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