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Leading a Best-Response Teammate in an Ad Hoc Team.
Peter Stone,
Gal A. Kaminka, and Jeffrey S. Rosenschein.
In
Esther David, Enrico Gerding, David Sarne, and Onn
Shehory, editors, Agent-Mediated Electronic Commerce: Designing Trading Strategies and Mechanisms for Electronic Markets,
pp. 132–146, Springer Verlag, November 2010.
Official version from publisher's
webpage
[PDF]179.3kB [postscript]226.4kB
Teams of agents may not always be developed in a planned, coordinated fashion. Rather, as deployed agents become more common in e-commerce and other settings, there are increasing opportunities for previously unacquainted agents to cooperate in ad hoc team settings. In such scenarios, it is useful for individual agents to be able to collaborate with a wide variety of possible teammates under the philosophy that not all agents are fully rational. This paper considers an agent that is to interact repeatedly with a teammate that will adapt to this interaction in a particular suboptimal, but natural way. We formalize this setting in game-theoretic terms, provide and analyze a fully-implemented algorithm for finding optimal action sequences, prove some theoretical results pertaining to the lengths of these action sequences, and provide empirical results pertaining to the prevalence of our problem of interest in random interaction settings.
@Incollection(AMEC09,
author="Peter Stone and Gal A.\ Kaminka and Jeffrey S.\ Rosenschein",
title="Leading a Best-Response Teammate in an Ad Hoc Team",
booktitle="Agent-Mediated Electronic Commerce: Designing Trading Strategies and Mechanisms for Electronic Markets",
editor="Esther David and Enrico Gerding and David Sarne and Onn Shehory",
month="November",
year="2010",
pages="132--146",
publisher="Springer Verlag",
abstract={Teams of agents may not always be developed in a planned, coordinated fashion. Rather, as deployed agents become more common in e-commerce and other settings, there are increasing opportunities for previously unacquainted agents to cooperate in ad hoc team settings. In such scenarios, it is useful for individual agents to be able to collaborate with a wide variety of possible teammates under the philosophy that not all agents are fully rational. This paper considers an agent that is to interact repeatedly with a teammate that will adapt to this interaction in a particular suboptimal, but natural way. We formalize this setting in game-theoretic terms, provide and analyze a fully-implemented algorithm for finding optimal action sequences, prove some theoretical results pertaining to the lengths of these action sequences, and provide empirical results pertaining to the prevalence of our problem of interest in random interaction settings.},
wwwnote={Official version from <a href="http://www.springer.com/business+%26+management/business+information+systems/book/978-3-642-15116-3">publisher's webpage</a>},
)
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