Nash Extremal Optimization and Large Cournot Games

  • Rodica Ioana Lung
  • Tudor Dan Mihoc
  • D. Dumitrescu
Part of the Studies in Computational Intelligence book series (SCI, volume 387)


Equilibria detection in large games represents an important challenge in computational game theory. A solution based on generative relations defined on the strategy set and the standard Extremal Optimization algorithm is proposed. The Cournot oligopoly model involving up to 1000 players is used to test the proposed methods. Results are compared with those obtained by a Crowding Differential Evolution algorithm.


Nash Equilibrium Differential Evolution Differential Evolution Algorithm Noncooperative Game Multimodal Optimization 
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  1. 1.
    Boettcher, S., Percus, A.G.: Optimization with Extremal Dynamics. Physical Review Letters 86, 5211–5214 (2001), doi:10.1103/PhysRevLett.86.5211CrossRefGoogle Scholar
  2. 2.
    Boettcher, S., Percus, A.G.: Extremal optimization: an evolutionary local-search algorithm. CoRR cs.NE/0209030 (2002)Google Scholar
  3. 3.
    Daughety, A.F.: Cournot oligopoly: characterization and applications. Cambridge University Press, Cambridge (1988)zbMATHGoogle Scholar
  4. 4.
    Ishibuchi, H., Tsukamoto, N., Nojima, Y.: Evolutionary many-objective optimization. In: 3rd International Workshop on Genetic and Evolving Systems, GEFS 2008, pp. 47–52 (2008), doi:10.1109/GEFS.2008.4484566Google Scholar
  5. 5.
    Lung, R.I., Dumitrescu, D.: Computing nash equilibria by means of evolutionary computation. Int. J. of Computers, Communications & Control III(suppl. issue), 364–368 (2008)Google Scholar
  6. 6.
    Lung, R.I., Mihoc, T.D., Dumitrescu, D.: Nash equilibria detection for multi-player games. In: IEEE Congress on Evolutionary Computation, pp. 1–5 (2010)Google Scholar
  7. 7.
    McKelvey, R.D., McLennan, A.: Computation of equilibria in finite games. In: Amman, H.M., Kendrick, D.A., Rust, J. (eds.) Handbook of Computational Economics, vol. 1, ch. 2, pp. 87–142. Elsevier, Amsterdam (1996)Google Scholar
  8. 8.
    Nash, J.F.: Non-cooperative games. Annals of Mathematics 54, 286–295 (1951)MathSciNetzbMATHCrossRefGoogle Scholar
  9. 9.
    Thomsen, R.: Multimodal optimization using crowding-based differential evolution. In: Proceedings of the 2004 IEEE Congress on Evolutionary Computation, pp. 1382–1389. IEEE Press, Portland (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Rodica Ioana Lung
    • 1
  • Tudor Dan Mihoc
    • 1
  • D. Dumitrescu
    • 1
  1. 1.Babes-Bolyai UniversityRomania

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