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A Neural Networks approach to Minority Game

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  • Luca Grilli
  • Angelo Sfrecola

Abstract

The minority game (MG) comes from the so-called “El Farol bar” problem by W.B. Arthur. The underlying idea is competition for limited resources and it can be applied to different fields such as: stock markets, alternative roads between two locations and in general problems in which the players in the “minority” win. Players in this game use a window of the global history for making their decisions, we propose a neural networks approach with learning algorithms in order to determine players strategies. We use three different algorithms to generate the sequence of minority decisions and consider the prediction power of a neural network that uses the Hebbian algorithm. The case of sequences randomly generated is also studied.

Suggested Citation

  • Luca Grilli & Angelo Sfrecola, 2009. "A Neural Networks approach to Minority Game," Quaderni DSEMS lg_nca_2009, Dipartimento di Scienze Economiche, Matematiche e Statistiche, Universita' di Foggia.
    • Handle: RePEc:ufg:qdsems:lg_nca_2009
    DOI: 10.1007/s00521-007-0163-1
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    References listed on IDEAS

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    1. Bernaschi, Massimo & Grilli, Luca & Vergni, Davide, 2002. "Statistical analysis of fixed income market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 308(1), pages 381-390.
    2. Arthur, W Brian, 1994. "Inductive Reasoning and Bounded Rationality," American Economic Review, American Economic Association, vol. 84(2), pages 406-411, May.
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    More about this item

    Keywords

    Minority game; Learning algorithms; Neural networks.;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General

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