Global optimization of minority game by intelligent agents

Competing intelligent search agents in global optimization

Intelligent game agents

The topic of getting machines to play classical board games at the same level as top ranking human players, is a research area of artificial intelligence that has received a considerably amount of attention from researchers during the years. But although the area to this point has received quite a lot of attention, and there exist examples of computers that has defeated top ranking human player...

Evolving intelligent game-playing agents

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Evolving Populations of Agents with Personalities in the Minority Game

In our daily lives we often have to face binary decisions where we seek to take the minority’s choice, e.g., in traffic scenarios where we have to choose between similar alternative routes. In previous papers, we have dealt with an agent coordination mechanism for binary decision models introduced in the literature recently: the El Farol Bar Problem. Extending this model, we have proposed perso...

Heterogeneous Populations of Learning Agents in the Minority Game

We study how a group of adaptive agents can coordinate when competing for limited resources. A popular game theoretic model for this is the Minority Game. In this article we show that the coordination among learning agents can improve when agents use different learning parameters or even evolve their learning parameters. Better coordination leads to less resources being wasted and agents achiev...