Uncertainty in Artificial Intelligence
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Efficient Nash Computation in Large Population Games with Bounded Influence
Michael Kearns, Yishay Mansour
We introduce a general representation of large-population games in which each player s influence ON the others IS centralized AND limited, but may otherwise be arbitrary.This representation significantly generalizes the class known AS congestion games IN a natural way.Our main results are provably correct AND efficient algorithms FOR computing AND learning approximate Nash equilibria IN this general framework.
Pages: 259-266
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PDF Link: /papers/02/p259-kearns.pdf
AUTHOR = "Michael Kearns and Yishay Mansour",
TITLE = "Efficient Nash Computation in Large Population Games with Bounded Influence",
BOOKTITLE = "Proceedings of the Eighteenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-02)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "2002",
PAGES = "259--266"

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