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A Neural Networks approach to Minority Game

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  • Luca Grilli
  • Angelo Sfrecola

Abstract

The Minority Game 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 the neural network associated to that algorithm. The case of sequences generated randomly is also studied.

Suggested Citation

  • Luca Grilli & Angelo Sfrecola, 2005. "A Neural Networks approach to Minority Game," Quaderni DSEMS 13-2005, Dipartimento di Scienze Economiche, Matematiche e Statistiche, Universita' di Foggia.
    • Handle: RePEc:ufg:qdsems:13-2005
    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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