Economic Data Analysis and Cooperative Information Control

R. Kamimura and S. Hahimoto (Japan)


Competition, cooperation, informationcontrol, economic analysis


This paper proposes a novel information theoretic ap proach to self-organization called cooperative information control. The method aims to mediate between competition and cooperation among neurons by controlling information content in neurons. Competition is realized by maximizing information content in neurons. In the process of informa tion maximization, only a small number of neurons win the competition, while all the others are inactive. Cooperation is implemented by having neurons behave similarly to their neighbors. These two processes are unified and controlled in the framework of cooperative information control. We applied the new method to the analysis of the Japanese economic data during 1990-2001. In the analysis, experi mental results confirmed that competition and cooperation are flexibly controlled, and clearer representations can be obtained.

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