Maximising Personal Utility Using Intelligent Strategy in Minority Game

摘要

In the traditional minority game, each agent chooses the highest-score strategy at every time step from its initial strategies which are allocated randomly. How can one agent manage to outperform its competitors and maximise its own utility in this competing and dynamic environment? In this paper, we study a version of the minority game in which one privileged agent is allowed to join the game with larger memory size and free to choose any strategy, while the other agents own small number of strategies. Simulations show that the privileged agent using the intelligent strategy outperforms the other agents in the same model and other models proposed in previous work in terms of individual payoff. We also investigate how the number of strategies and the length of memory affect the privileged agent's performance.