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Net Journal 6

Creating a new field of engineering using a self-learning, self-evolving system - The development of applications useful in the real world is highly expected.

Masashi Furukawa, Doctor of Engineering

Masashi Furukawa, Doctor of Engineering,
Professor of the Graduate School of Information Science and Technology, Hokkaido University,
Division of Synergetic Information Science's Research Group of Complex Systems Engineering

Striving to elucidate the rules and mechanisms present in a complex world through an engineering approach

---- Recently, the term "complex" has been used in various contexts. How does complex systems engineering relate to our daily lives?

Dr. Furukawa: If we say, "The world where we live is complex," most people would respond, "Exactly." Modern society is nothing less than chaotic, with problems defying conventional wisdom and methodology appearing everywhere in the world. The Research Group of Complex Systems Engineering aims to establish new sciences and engineering techniques by addressing such problems from four viewpoints - autonomous systems engineering, harmonious systems engineering, formative systems engineering and chaotic systems engineering. In autonomous systems engineering, we are studying a mechanism in which natural systems and systems of artifacts learn and evolve while controlling themselves. System components cognize their surroundings in their respective environments, make judgments, determine their actions and act. The results of their actions interrelate with other components and affect the components per se, causing the entire system, including the components, to emerge as something new and evolve. This is an ordinary occurrence in the natural world, but the same thing happens in the world of artifacts. For example, the Internet is a man-made artifact, but its components, i.e. Websites and users, act in a self-serving and autonomous manner, leading the evolution and development of the network as a whole. Complex systems like this have something very similar to the laws of nature. The theme of the Laboratory of Autonomous Systems Engineering is to elucidate new theories and methodologies and use them to facilitate the development of self-learning and self-evolving computers, robots and so forth.

Analogy of Web networks to a human brain - Global Scale Brain

---- What kind of research programs are being pursued at the Laboratory of Autonomous Systems Engineering?

Dr. Furukawa: Currently, three major projects are under way. One aims to study the analyses and applications of complex networks. A network is comprised of nodes (points) and links connecting nodes. A complicated network has hundreds of millions of nodes to billions of nodes, of which the individual relations and behaviors differ. For example, the human brain has more than 14 billion nodes (brain neurons) and the total number of link combinations amounts to 109-10 (10 to the 9th or 10th power). Furthermore, the World Wide Web has more than 50 billion nodes, in the form of Websites and homepages, which are interconnected by countless links. It is impossible to investigate the properties of a gigantic, complicated network like this one by enumerating all relations. Therefore, statistical methods came to be employed, followed by the appearance of theories such as the small world and scale-free networks (Ex. 1).

This project regards the World Wide Web as the Global Scale Brain and is striving to shed light on the characteristics of the network as well as the intelligence the network produces by using graph theory, evolving and learning agent technology, self-organization mapping and other methodologies. Among other aspects, we have focused on human behavior (behavioral patterns) and have made considerable achievements in software development geared to learn user behavior, leading to the establishment of a university-launched venture business providing trendsetting Web services.

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