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Patrick Riley and Manuela Veloso. Recognizing
Probabilistic Opponent Movement Models. In A. Birk, S. Coradeschi, and S. Tadokoro, editors, RoboCup-2001: Robot Soccer
World Cup V, number 2377 in Lecture Notes in Artificial Intelligence, pp. 453–458, Springer Verlag, Berlin, 2002.
(extended abstract)
Publisher's Webpage© Springer-Verlag
In multiagent adversarial domains, team agents should adapt to the environment and opponent. We introduce a model representation as part of a planning process for a simulated soccer domain. The planning is centralized, but the plans are executed in a multi-agent environment, with teammate and opponent agents. Further, we present a recognition algorithm where the model which most closely matches the behavior of the opponents can be selected from few observations of the opponent. Empirical results are presented to verify that important information is maintained through the abstraction the models provide.
@InCollection(LNAI01-coach,
Author = "Patrick Riley and Manuela Veloso",
Title = "Recognizing Probabilistic Opponent Movement Models",
booktitle = "{R}obo{C}up-2001: Robot Soccer World Cup {V}",
Editor = "A. Birk and S. Coradeschi and S. Tadokoro",
Publisher = "Springer Verlag",
series = {Lecture Notes in Artificial Intelligence},
number = {2377},
pages = {453--458},
address = "Berlin",
year = "2002",
note = {(extended abstract)},
wwwnote = {<a href="http://www.springer.de/comp/lncs/index.html">Publisher's Webpage</a>© Springer-Verlag},
abstract = {In multiagent adversarial domains, team agents
should adapt to the environment and opponent. We
introduce a model representation as part of a
planning process for a simulated soccer domain. The
planning is centralized, but the plans are executed
in a multi-agent environment, with teammate and
opponent agents. Further, we present a recognition
algorithm where the model which most closely matches
the behavior of the opponents can be selected from
few observations of the opponent. Empirical results
are presented to verify that important information
is maintained through the abstraction the models
provide.},
bib2html_pubtype = {Refereed Conference},
bib2html_rescat = {Coaching,Opponent and Teammate Modeling},
bib2html_funding = {NSF,CoABS,ActiveTemplates},
)
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