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<article-title>Factoring Games to Isolate Strategic Interactions</article-title>
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<author><a href="mailto:gbd@cs.cmu.edu"><name>George B. Davis</name></a></author>
<aff>School of Computer Science, Carnegie Mellon University</aff>

<author><a href="mailto:mbenisch@cs.cmu.edu"><name>Michael Benisch</name></a></author>
<aff>School of Computer Science, Carnegie Mellon University</aff>

<author><a href="mailto:carley@cs.cmu.edu"><name>Kathleen M. Carley</name></a></author>
<aff>School of Computer Science, Carnegie Mellon University</aff>

<author><a href="mailto:sadeh@cs.cmu.edu"><name>Norman M. Sadeh</name></a></author>
<aff>School of Computer Science, Carnegie Mellon University</aff>
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<title>ABSTRACT</title>
<p>Game theoretic reasoning about multi-agent systems has
been made more tractable by algorithms that exploit various
types of independence in agents' utilities. However, previous
work has assumed that a game's precise independence structure is given in advance. This paper addresses the problem
of finding independence structure in a general form game
when it is not known ahead of time, or of finding an approximation when full independence does not exist. We give an
expected polynomial time algorithm to divide a bounded-
payout normal form game into factor games that isolate independent strategic interactions. We also show that the best
<italic>approximate</italic> factoring can be found in polynomial time for
a specific interaction that is not fully independent. Once
known, factors aide computation of game theoretic solution
concepts, including Nash equilibria (or &#949;-equilibria for approximate factors), in some cases guaranteeing polynomial
complexity where previous bounds were exponential.</p>
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