Science driven by high-dimensional data has been proposed and advanced considerably, but the difficulty of creating a theory to accompany it is gradually being recognized. For example, we often end up with research that focuses on the methodology of machine learning, away from the original interest of natural phenomena. Here, we propose a theory of collective intelligence by tracking both living and non-living agents, starting from the essential question of what life is. Herein lies the creativity of this project, which is a new and challenging task, different from other big data analysis and biological research. In the past, when data was scarce, research was conducted by spinning a plausible story with a "small model" (in the sense of a small number of parameters and degrees of freedom). The challenge here is to create a new theory of life by profiling the individual agents that make up the collective and by using powered agent simulations using deep learning techniques. The result should have a profound impact on both artificial life and multi-agent machine learning.

9:00 - 9:10 Opening Remark

9:10 - 9:50 Nobuaki Mizumoto TBA

10:00 -12:00 ANT session

Shigeto Dobata “Spontaneous aggregation behaviors in the ant Pristomyrmex punctatus”

Norihiro Maruyama ” Epsilon Machine Analysis of Ants behavior”

11:30 - 12:00 Discussion

12:00 -14:00 Lunch

14:00 - 14:40 Takashi Shimada “On the Robustness and Plasticity of ``Ecosystems’'

14:50 - 16:20 Ciliate session

Akiko Kashiwagi “Fluctuations of the gene expression in populations of Tetrahymena thermophila”

Hiroki Kojima & Takashi Ikegami “Phenotypic Inheritance of Dynamical traits in growing populations of Tetrahymena thermophila”

Coffee Break

16:30 - 18:00 WEB session

Yasuhiro Hashimoto “Beyond Preferential Attachment: Popularity Fluctuations and Their Sources”

fumiko ogushi “Characterization of the Digital Knowledge Ecosystem of Wikipedia”

18:00 -18:30 Wrap up

Takashi Ikegami , University of Tokyo (TSVP Visiting Scholar)