A Neural Networks approach to Minority Game
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.
|Date of creation:||Oct 2009|
|Date of revision:|
|Publication status:||Published in Neural Computing and Applications, Vol. 18, n. 2, pp. 109-113, Feb. 2009.|
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- Massimo Bernaschi & Luca Grilli & Davide Vergni, 2002.
"Statistical analysis of fixed income market,"
lg_physa_2002, Dipartimento di Scienze Economiche, Matematiche e Statistiche, Universita' di Foggia.
- 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.
- Arthur, W Brian, 1994. "Inductive Reasoning and Bounded Rationality," American Economic Review, American Economic Association, vol. 84(2), pages 406-11, May.
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