We live in a world filled with a variety of life forms, societies, and natural phenomena. When we look at these realities from the perspective of an information management system, we can gain much insight into systems operations, system designs, and how various things are accomplished. At the same time, the various phenomena trigger our curiosity as to how they all work. (Image 1)
In our lab, our research focuses on creating models based on life, societies, and natural phenomena, and through simulation and analysis tries to gain useful insights for building an information-processing system. (Image 2) Modeling refers to extracting the essence of the phenomenon we are observing and refining it to match the intended purpose. In this research we occasionally face difficult challenges in approaching the essence of a phenomenon and developing new information-processing systems. Going to the heart of a phenomenon and contemplating the gained insights relating to the information-processing system are, in fact, two sides of the same coin, and are necessary to gain even deeper insights.
Here are some of the topics we are working on in our lab. The subjects are only briefly touched on here, but more detailed information can be found by selecting from the left-hand menu. The use of cellular automaton is one of the ways we can create and analyze models for a variety of natural phenomena. People in the field of cellular automata study patterns seen in a variety of phenomena and their underlying mechanisms from the perspective of information management.
Game theory and multi-agent systems are some of the ways we can analyze systems with multiple subjects, objects or individuals interacting with one another. An example approach from game theory is to have a large-scale computer network defend against the spread of computer viruses and to research mechanisms for multiple computers to cooperate and operate more efficiently.
Magic squares and the Stable Marriage Problem (SMP) are one of the typical combinatorial problems. In relation to magic squares, we add in elements of time to propose new dynamic squares, and we consider their nature. In regards to SMP, we use graphs to visualize what happens and study what we could understand about its nature from visualization. In both cases, we seek to gain new insights by looking at the structure of the problems.
In genetic algorithms, we incorporate the perspective of diversity into the process of calculation to study potential methods for obtaining optimal solutions. Diverse organisms, including humans, are thought to have evolved through natural selection. By introducing the concept of species into this process of evolution, we avoid localization of the solution and instead seek the optimal solution.
Here we introduce some of our research examples. In our laboratory, we try not only to learn from life, society, and natural phenomena, but we also strive to make contributions to the information and related fields through our research.