• Sorted by Date • Classified by Publication Type • Classified by Research Category •
Patrick Riley and Manuela Veloso. Coaching
Advice and Adaptation. In Daniel Polani, Andrea Bonarini, Brett Browning, and Kazuo Yoshida, editors, RoboCup-2003: The
Sixth RoboCup Competitions and Conferences, Springer Verlag, Berlin, 2004. (to appear)
Publisher's Webpage© Springer-Verlag
Our research on coaching refers to one autonomous agent providing advice to another autonomous agent about how to act. In past work, we dealt with advice-receiving agents with fixed strategies, and we now consider agents which are learning. Further, we consider agents which have various limitations, with the hypothesis that if the coach adapts its advice to those limitations, more effective learning will result. In this work, we systematically explore the effect of various limitations upon the effectiveness of the coach's advice. We state the two learning problems faced by the coach and the coached agents, and empirically study these problems in a predator-prey environment. The coach has access to optimal policies for the environment, and advises the predator on which actions to take. We experiment with limitations on the predator agent's actions, the bandwidth between the coach and agent, and the memory size of the agent. We analyze the results which show that coaching can improve agent performance in the face of all these limitations.
@InCollection(LNAI03-predprey,
Author = "Patrick Riley and Manuela Veloso",
Title = {Coaching Advice and Adaptation},
booktitle = "{R}obo{C}up-2003: The Sixth {R}obo{C}up Competitions
and Conferences",
Editor = {Daniel Polani and Andrea Bonarini and Brett Browning and Kazuo Yoshida},
Publisher = "Springer Verlag",
address = "Berlin",
year = 2004,
wwwnote = {<a
href="http://www.springer.de/comp/lncs/index.html">Publisher's Webpage</a>© Springer-Verlag},
note = {(to appear)},
abstract = { Our research on coaching refers to one autonomous
agent providing advice to another autonomous agent
about how to act. In past work, we dealt with
advice-receiving agents with fixed strategies, and
we now consider agents which are learning. Further,
we consider agents which have various limitations,
with the hypothesis that if the coach adapts its
advice to those limitations, more effective learning
will result. In this work, we systematically explore
the effect of various limitations upon the
effectiveness of the coach's advice. We state the
two learning problems faced by the coach and the
coached agents, and empirically study these problems
in a predator-prey environment. The coach has access
to optimal policies for the environment, and advises
the predator on which actions to take. We experiment
with limitations on the predator agent's actions,
the bandwidth between the coach and agent, and the
memory size of the agent. We analyze the results
which show that coaching can improve agent
performance in the face of all these limitations.},
bib2html_pubtype ={Refereed Conference},
bib2html_rescat ={Coaching},
bib2html_funding = {NSF,CoABS,ActiveTemplates},
)
Generated by bib2html.pl (written by Patrick Riley ) on Thu Mar 31, 2005 16:21:00