We have investigated economic systems and the brain as complex systems from a viewpoint of artificial intelligence, by using our experience on applied mathematics and computation. Our major topics are Econophysics, Human Random Generation, Application of Neural Programming to Noninvasive Diagnosis, and Cooperation of Agents, out of which we devoted most of our effort to Econophysics.
We focused on studying the statistical properties of high frequency data in finance (HFDF) an also modeling of artificial markets, both being emerging fields in frontier of science. In the course of study, we have discovered that the critical region in the parameter space of our model corresponds to the real high-frequency financial data, by showing that both have the Levy distribution of the same size of indices. This result was published in INFORMATION journal in 2001 and in Empirical Science of Financial Fluctuations (Springer, 2002) which is the proceedings of the first conference in Econophysics held in 2000. We have also studied HFDF by fast computer in detail to clarify the controversial analogy between well-developed turbulence and foreign currency exchange, and also found short-term predictability based on stable patterns observed, as well as the triangle arbitrage chances and its relaxation time. We have made various presentations in domestic meetings and international conferences and made two oversea travels including Joint Conference on Information Sciences in 2000 and an informal seminar at Santa Fe Institute in 2002.
In the study of Human Random Generation, we have shown, by analyzing the time series of newly taken data from our six students, that it is possible to incorporate characteristics of individuals to model parameters that distinguish the differences of those individuals.
Neural Network Application to Noninvasive diagnosis is a joint work with Dr. Satoshi Yoshida, on which we submitted an application for patent in 2001.