著者

池上 高志 岡 瑞起 橋本 康弘

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.30, no.6, pp.811-819, 2015-11-01 (Released:2017-09-07)

参考文献数

24

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The Web is perhaps the most complex system that we know today. Its massive scale, complex dynamism, open richness, and social character mean that it may be more profitable to study it by using tools and concepts appropriate for understanding nervous systems, organisms, ecosystems and society, rather than approaches more traditionally employed to study engineering technology. Simultaneously, the scientists trying to understand this wide array of complex natural systems may have much to gain by considering the emerging study of the Web. In this paper, taking examples from our recent studies on the Web, we concretely discuss the relevance of the Web as a large model, as opposed to small models often used in physics or biology, for understanding living systems. An idea is forwarded of a default mode network that introduces autonomy, evolvability and homeostasis into the Web. For example, we argue for the existence of two modes of the states in Twitter; the excitation and baseline. The Web turns out to be an excitable media similar to a brain or certain kinds of chemical systems. R. Ashby's laws of requisite variety is also revisited to study its relevance in the light of controlling complex systems.