Individual agent's wealth in minority games Online publication date: Fri, 26-Jun-2009
by Yingni She, Ho-Fung Leung
International Journal of Autonomous and Adaptive Communications Systems (IJAACS), Vol. 2, No. 3, 2009
Abstract: In the traditional minority game, each agent chooses the highest-score predictor at every time step from its initial predictors which are allocated randomly. In this paper, we study a version of the minority game in which one individual privileged agent is allowed to join the game with different memory size from the other agents and free to choose any predictor, while each of the other agents owns small number of predictors. We investigate the privileged agent's wealth in different dynamic environments. Simulations show that the privileged agent using the proposed intelligent strategy can outperform the other agents in the same model and other models proposed in previous work in terms of individual wealth. We also discuss the impacts of the parameters on the privileged agent's wealth, such as the number of predictors the privileged agent owns and its memory size. Moreover, we discuss the impact of the number of predictors the other agents possess and their memory sizes on the privileged agent's wealth.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Autonomous and Adaptive Communications Systems (IJAACS):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com