Neural Computing and Applications

, Volume 18, Issue 2, pp 109–113 | Cite as

A neural networks approach to minority game

Original Article

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.

Keywords

Minority game Learning algorithms Neural networks 

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Copyright information

© Springer-Verlag London Limited 2007

Authors and Affiliations

  1. 1.Dipartimento di Scienze Economiche, Matematiche e StatisticheUniversità degli Studi di FoggiaFoggiaItaly

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