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Peter Stone, Gal A. Kaminka,
and Jeff S. Rosenschein. Leading a Best-Response Teammate in an Ad Hoc
Team. In Esther David, E. Gerding, David Sarne, and Onn Shehory, editors,
Agent-Mediated Electronic Commerce. Designing Trading Strategies and Mechanisms for Electronic Markets. AMEC 2009, TADA
2009, Lecture Notes in Business Information Processing, pp. 132–146, Springer, Berlin, Heidelberg, 2010.
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 Jeff 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. AMEC 2009, TADA 2009},
OPTcrossref = {},
OPTkey = {},
pages = {132--146},
year = {2010},
editor = {Esther David and Gerding, E. and Sarne, David and Shehory, Onn},
volume = {59},
OPTnumber = {},
series = {Lecture Notes in Business Information Processing},
address = {Berlin, Heidelberg},
OPTmonth = {},
OPTorganization = {},
publisher = {Springer},
OPTnote = {},
OPTannote = {},
OPTurl = {https://doi.org/10.1007/978-3-642-15117-0_10},
OPTdoi = {},
OPTissn = {},
OPTlocalfile = {},
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 = {},
}
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