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.
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机译：少数游戏（MG）来自W.B.所谓的“ El Farol bar”问题。亚瑟。潜在的想法是争夺有限的资源，它可以应用于不同的领域，例如：股票市场，两个地点之间的替代道路以及“少数派”参与者获胜的一般性问题。游戏中的玩家使用全球历史的窗口来做出决定，我们提出了一种具有学习算法的神经网络方法，以确定玩家的策略。我们使用三种不同的算法来生成少数决策的序列，并考虑使用Hebbian算法的神经网络的预测能力。还研究了随机生成序列的情况。
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