A Neural Networks approach to Minority Game

Luca Grilli and Angelo Sfrecola ()

Quaderni DSEMS from Dipartimento di Scienze Economiche, Matematiche e Statistiche, Universita' di Foggia

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. (search for similar items in EconPapers)
Date: 2009-10
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Published in Neural Computing and Applications, Vol. 18, n. 2, pp. 109-113, Feb. 2009.

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http://dx.doi.org/10.1007/s00521-007-0163-1

Related works:
Working Paper: A Neural Networks approach to Minority Game (2005)
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Persistent link: https://EconPapers.repec.org/RePEc:ufg:qdsems:lg_nca_2009

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