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@InProceedings{AAAI06-coach,
author="Gregory Kuhlmann and William B.\ Knox and Peter Stone",
title="Know Thine Enemy: A Champion {R}obo{C}up Coach Agent",
booktitle="Proceedings of the Twenty-First National Conference on Artificial Intelligence",
month="July",year="2006",
pages="1463--68",
abstract={
In a team-based multiagent system, the ability to
construct a model of an opponent team's joint
behavior can be useful for determining an agent's
expected distribution over future world states, and
thus can inform its planning of future actions.
This paper presents an approach to team opponent
modeling in the context of the RoboCup simulation
coach competition. Specifically, it introduces an
autonomous coach agent capable of analyzing past
games of the current opponent, advising its own team
how to play against this opponent, and identifying
patterns or weaknesses on the part of the opponent.
Our approach is fully implemented and tested within
the RoboCup soccer server, and was the champion of
the RoboCup 2005 simulation coach competition.
},
wwwnote={AAAI 2006},
}