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Inon Zuckerman, Sarit Kraus, Jeffrey
S. Rosenschein, and Gal A. Kaminka. An Adversarial Environment Model
for Bounded Rational Agents in Zero-Sum Interactions. In Proceedings of the Sixth International Joint Conference on
Autonomous Agents and Multi-Agent Systems (AAMAS-07), 2007.
Multiagent environments are often not cooperative nor collaborative; in many cases, agents have conflicting interests, leading to adversarial interactions. This paper presents a formal Adversarial Environment model for bounded rational agents operating in a zero-sum environment. In such environments, attempts to use classical utility-based search methods can raise a variety of difficulties (e.g., implicitly modeling the opponent as an omniscient utility maximizer, rather than leveraging a more nuanced, explicit opponent model). We define an Adversarial Environment by describing the mental states of an agent in such an environment. We then present behavioral axioms that are intended to serve as design principles for building such adversarial agents. We explore the application of our approach by analyzing log files of completed Connect-Four games, and present an empirical analysis of the axioms' appropriateness.
@InProceedings{aamas07inon,
author = {Inon Zuckerman and Sarit Kraus and Jeffrey S. Rosenschein and Gal A. Kaminka},
title = {An Adversarial Environment Model for Bounded Rational Agents in Zero-Sum Interactions},
OPTcrossref = {},
OPTkey = {},
booktitle = AAMAS-07,
OPTpages = {In press},
year = {2007},
abstract = {
Multiagent environments are often not cooperative nor collaborative;
in many cases, agents have conflicting interests, leading to
adversarial interactions. This paper presents a formal
Adversarial Environment model for bounded rational agents
operating in a zero-sum environment. In such environments, attempts
to use classical utility-based search methods can raise a variety of
difficulties (e.g., implicitly modeling the opponent as an
omniscient utility maximizer, rather than leveraging a more nuanced,
explicit opponent model). We define an Adversarial Environment by describing
the mental states of an agent in such an environment. We then present behavioral
axioms that are intended to serve as design principles for building
such adversarial agents. We explore the application of our approach
by analyzing log files of completed Connect-Four games, and present
an empirical analysis of the axioms' appropriateness.
},
wwwnote = {},
OPTeditor = {},
OPTvolume = {},
OPTnumber = {},
OPTseries = {},
OPTaddress = {},
OPTmonth = {},
OPTorganization = {},
OPTpublisher = {},
OPTannote = {}
}
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