Abstract
Generally, in multi-agent systems, there are close relations between behavior of each individual agent and the group of agents as a whole, so a certain information about the relative state of each agent in the group may be hided in each agent behavior. If this information can be extracted, each agent has the possibility to improve its state by seeing only its own behavior without seeing other agents’ behaviors. In this paper, we focus on “power-law” which is interesting character seen in the behavior of each node of various kinds of networks as one of such information. Up to now, we have already found that power-law can be seen in the efficiently behaving agents in Minority Game which is the competitive multi-agent simulation environment. So, in this paper we have verified whether it is possible for each agent in the game to improve its state by seeing only its own behavior, and confirmed that the performance gain was actually possible.
Keyword: Minority game, Indirect coordination, Power law.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Barabasi, A.: Linked: How Everything Is Connected to Everything Else and What It Means, Reissue edn. Plume Books (2003)
Fukuda, K., Takayasu, M., Takayasu, H.: Analysis of Minimal Model of Internet Traffic. In: Fukui, M., Sugiyama, Y., Schreckenberg, M., Wolf, D.E. (eds.) Traffic and Granular Flow 2001. Springer, Heidelberg (2002)
Challet, D., Marsili, M., Zecchina, R.: Phase Transition in a Toy market (1999); on the major Minority Game web site: http://www.unifr.ch/econophysics/minority/
Li, Y., et al.: Evolution in Minority Games I. Games with a Fixed Strategy Space; on the major Minority Game web site, http://www.unifr.ch/econophysics/minority/
Kurihara, S., Fukuda, K., Hirotsu, T., Akashi, O., Sato, S., Sugawara, T.: Simple but efficient collaboration in a complex competitive situation. In: Proceedings of International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2003), pp. 1042–1043 (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kurihara, S., Fukuda, K., Sato, S., Sugawara, T. (2005). Effective Decision Making by Self-evaluation in the Multi-agent Environment. In: Deng, X., Ye, Y. (eds) Internet and Network Economics. WINE 2005. Lecture Notes in Computer Science, vol 3828. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11600930_63
Download citation
DOI: https://doi.org/10.1007/11600930_63
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30900-0
Online ISBN: 978-3-540-32293-1
eBook Packages: Computer ScienceComputer Science (R0)