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Computing Nash Equilibria of Action-Graph Games via Support Enumeration

  • David R. M. Thompson
  • Samantha Leung
  • Kevin Leyton-Brown
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7090)

Abstract

The support-enumeration method (SEM) for computation of Nash equilibrium has been shown to achieve state-of-the-art empirical performance on normal-form games. Action-graph games (AGGs) are exponentially smaller than the normal form on many important classes of games. We show how SEM can be extended to the AGG representation, yielding an exponential improvement in worst-case runtime. Empirically, we demonstrate that our AGG-optimized SEM algorithm substantially outperforms the original SEM, and also outperforms state-of-the-art AGG-optimized algorithms on most problem distributions.

Keywords

Nash Equilibrium Congestion Game Empirical Performance Graphical Game Proof Sketch 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • David R. M. Thompson
    • 1
  • Samantha Leung
    • 2
  • Kevin Leyton-Brown
    • 1
  1. 1.University of British ColumbiaCanada
  2. 2.Cornell UniversityUSA

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