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Playing large games using simple strategies

Published:09 June 2003Publication History

ABSTRACT

We prove the existence of ε-Nash equilibrium strategies with support logarithmic in the number of pure strategies. We also show that the payoffs to all players in any (exact) Nash equilibrium can be ε-approximated by the payoffs to the players in some such logarithmic support ε-Nash equilibrium. These strategies are also uniform on a multiset of logarithmic size and therefore this leads to a quasi-polynomial algorithm for computing an ε-Nash equilibrium. To our knowledge this is the first subexponential algorithm for finding an ε-Nash equilibrium. Our results hold for any multiple-player game as long as the number of players is a constant (i.e., it is independent of the number of pure strategies). A similar argument also proves that for a fixed number of players m, the payoffs to all players in any m-tuple of mixed strategies can be ε-approximated by the payoffs in some m-tuple of constant support strategies.We also prove that if the payoff matrices of a two person game have low rank then the game has an exact Nash equilibrium with small support. This implies that if the payoff matrices can be well approximated by low rank matrices, the game has an ε-equilibrium with small support. It also implies that if the payoff matrices have constant rank we can compute an exact Nash equilibrium in polynomial time.

References

  1. I. Althöfer. On sparse approximations to randomized strategies and convex combinations. Linear Algebra and Applications, 199:339--355, 1994.Google ScholarGoogle ScholarCross RefCross Ref
  2. V. Conitzer and T. Sandholm. Complexity results about nash equilibria. In International Joint Conference on Artificial Intelligence, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. A. Czumaj and B. Voecking. Tight bounds for worst-case equilibria. In Annual ACM-SIAM Symposium on Discrete Algorithms, pages 413--420, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. N. Devanur and N. Vishnoi. Private communication, 2003.Google ScholarGoogle Scholar
  5. I. Gilboa and E. Zemel. Nash and correlated equilibria: Some complexity considerations. Games and Economic Behavior, 15(5):745--770, 1989.Google ScholarGoogle Scholar
  6. M. D. Hirsch, C. H. Papadimitriou, and S. A. Vavasis. Exponential lower bounds for finding brouwer fixed points. Journal of Complexity, 5:379--416, 1989. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. W. Hoeffding. Probability inequalities for sums of bounded random variables. American Statistical Journal, pages 13--30, March 1963.Google ScholarGoogle ScholarCross RefCross Ref
  8. A. P. Jurg. Some topics in the theory of bimatrix games. www.ub.rug.nl/eldoc/dis/non-rug/a.p.jurg/.Google ScholarGoogle Scholar
  9. M. J. Kearns, M. L. Littman, and S. P. Singh. Graphical models for game theory. In UAI, pages 253--260, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. M. J. Kearns and Y. Mansour. Efficient nash computation in large population games with bounded influence. In UAI, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. D. Koller and N. Megiddo. Finding mixed strategies with small support in extensive form games. International Journal of Game Theory, 25:73--92, 1996.Google ScholarGoogle ScholarCross RefCross Ref
  12. D. Koller, N. Megiddo, and B. von Stengel. Fast algorithms for finding randomized strategies in game trees. In Annual ACM Symposium on the Theory of Computing, pages 750--759, 1994. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. D. Koller, N. Megiddo, and B. von Stengel. Efficient computation of equilibria for extensive two-person games. Games and Economic Behavior, 14(2):247--259, 1996.Google ScholarGoogle ScholarCross RefCross Ref
  14. E. Koutsoupias and C. H. Papadimitriou. Worst case equilibria. In Annual IEEE Symposium on Theoretical Aspects of Computer Science, pages 404--413, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. H. W. Kuhn. An algorithm for equilibrium points in bimatrix games. In Proceedings of the National Academy of Sciences, pages 1657--1662, 1961.Google ScholarGoogle ScholarCross RefCross Ref
  16. C. E. Lemke. Bimatrix equilibrium points and mathematical programming. Management Science, 11:681--689, 1965.Google ScholarGoogle ScholarCross RefCross Ref
  17. C. E. Lemke and J. T. Howson. Equilibrium points of bimatrix games. Journal of the Society for Industrial and Applied Mathematics, 12:413--423, 1964.Google ScholarGoogle ScholarCross RefCross Ref
  18. R. J. Lipton and N. Young. Simple strategies for zero-sum games with applications to complexity theory. In 26th ACM Symposium on the Theory of Computing, pages 734--740, 1994. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. M. L. Littman, M. J. Kearns, and S. P. Singh. An efficient, exact algorithm for solving tree-structured graphical games. In NIPS, pages 817--823, 2001.Google ScholarGoogle Scholar
  20. O. L. Mangasarian. Equilibrium points of bimatrix games. Journal of the Society for Industrial and Applied Mathematics, 12(4):778--780, 1964.Google ScholarGoogle ScholarCross RefCross Ref
  21. R. McKelvey and A. McLennan. Computation of equilibria in finite games. Amman, H., Kendrick, D., Rust, J. eds, Handbook of Computational Economics, 1, 1996.Google ScholarGoogle Scholar
  22. J. F. Nash. Non-cooperative games. Annals of Mathematics, 54:286--295, 1951.Google ScholarGoogle ScholarCross RefCross Ref
  23. C. H. Papadimitriou. On the complexity of the parity argument and other inefficient proofs of existence. Journal of Computer and System Sciences, 48(3), 1994. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. C. H. Papadimitriou. Algorithms, games, and the internet. In Annual ACM Symposium on the Theory of Computing, pages 749--753, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. T. E. S. Raghavan. Completely mixed strategies in bimatrix games. Journal of London Math Society, 2(2):709--712, 1970.Google ScholarGoogle ScholarCross RefCross Ref
  26. J. Rosenmuller. On a generalization of the lemke-howson algorithm to non-cooperative games. SIAM Journal of Applied Mathematics, 21:73--79, 1971.Google ScholarGoogle ScholarCross RefCross Ref
  27. T. Roughgarden and E. Tardos. How bad is selfish routing. In Annual IEEE Symposium on Foundations of Computer Science, pages 93--102, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. A. Rubinstein. Modeling Bounded Rationality. MIT Press, Cambridge, Massachusetts, 1998.Google ScholarGoogle Scholar
  29. H. Scarf. The approximation of fixed points of a continuous mapping. SIAM Journal of Applied Mathematics, 15:1328--1343, 1967.Google ScholarGoogle ScholarCross RefCross Ref
  30. H. Simon. Models of Bounded Rationality, Volume 2. MIT Press, Cambridge, Massachusetts, 1982.Google ScholarGoogle Scholar
  31. A. Vetta. Nash equilibria in competitive societies with applications to facility location, traffic routing and auctions. In Annual IEEE Symposium on Foundations of Computer Science, pages 416--425, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. B. von Stengel. Computing equilibria for two-person games. Aumann, R. and Hart, S. eds, Handbook of Game Theory, 3, 2002.Google ScholarGoogle Scholar
  33. I. Wilson. Computing equilibria of n-person games. SIAM Journal of Applied Mathematics, 21:80--87, 1971.Google ScholarGoogle ScholarCross RefCross Ref

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    • Published in

      cover image ACM Conferences
      EC '03: Proceedings of the 4th ACM conference on Electronic commerce
      June 2003
      292 pages
      ISBN:158113679X
      DOI:10.1145/779928

      Copyright © 2003 ACM

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      Publication History

      • Published: 9 June 2003

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