Peter Stone's Selected Publications

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Know Thine Enemy: A Champion RoboCup Coach Agent

Gregory Kuhlmann, William B. Knox, and Peter Stone. Know Thine Enemy: A Champion RoboCup Coach Agent. In Proceedings of the Twenty-First National Conference on Artificial Intelligence, pp. 1463–68, July 2006.
AAAI 2006

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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.

BibTeX Entry

@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={<a href="http://www.aaai.org/Conferences/AAAI/aaai06.php">AAAI 2006</a>},
}

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