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Graduate School of Science and Engineering
Information and Computer Science

Socio-informatics Laboratory

Website of the Laboratory 【In Japanese】

Designing relationality


Katsunori SHIMOHARA [Professor]

Acceptable course
Master's degree course
Doctoral degree course
Telephone : +81-774-65-6973
Office : KC-222
Database of Researchers
Ivan TANEV [Associate Professor]

Acceptable course
Master's degree course
Doctoral degree course
Telephone : +81-774-65-6699
Office : KC-223
Database of Researchers

Research Topics

Multi-agent systems:
Modelling and analyzing the emergent properties of population systems such as organization, economy and society
Network dynamics:
Investigating the meaning and function of human network in socio-economic systems
Community Design:
Visualizing and managing relationality assets as trust enabling rebuilding of communities
Software evolution:
Developing intelligent software systems by artificial evolutions
Driving agents:
For future autonomous vehicles that assist and cooperate with a human driver
Snake-like robots:
Advanced robots that autonomously evolve adaptive behaviors to their environment
Human Robot/Agent Interaction:
Investigating the meaning and function of communications with robots/agents as cohabitants in near future
Boundary and Relationality Perspective Systems Approach:
Investigating boundary-mediated and/or relationality-oriented systems approach for future system-of-systems

Research Contents

In research on “Designing Relationality”, we intend to investigate the significance and meaning of creating relationality through grasping, expressing and operating relationality as networks in the field of system science. Especially we focus on complex systems with emergent mechanisms. In other words, we are aiming to understand the significance and functions of such complex systems from a viewpoint of relationality.
The concept of relationality here denotes interactions through which two entities mutually influence each other, linkage over time and space, and context as a result of accumulated interactions and linkage. We human beings should be entities that wish for relationality or relationships with others and hope to find meaning in these relationships. Human beings, in other words, might live in relationality and be alive with relationality. Relationality is not limited to physical and spatial one, or rather basically invisible and information-driven, and sometimes ecological and environmental. Social and economic systems, culture, region, and senses of value, therefore, are included in the relationality.
Socio-informatics is an academic field in which we try to understand information-mediated interactions between humans, ‘Mono’ as tangible and physically perceived thing/entity, and ‘Koto’ as intangible and cognitively conceived thing/entity in adaptive complex systems by grasping a system as dynamic and self-organizing processes such as emergence, growth, development, fusion, fragmentation, and/or collapse of relationality network.
The topics of research include analysis of relationality between entities and the resulting emergent properties of complex systems and societies at various levels of hierarchy, from the lowest, molecular level through the DNA, cells to the highest level ― artificial and human societies.
Methodologies we have employed for relationality design are evolutionary computation, especially genetic programming, to imitate the mechanism of biological evolution on computers, and network science to visualize and analyze relationality as networks.
In socio-informatics, we are clarifying the meaning and significance of relationality-oriented systems, devising methodologies to create and facilitate such systems, and pursuing social information infrastructure where people can feel mental affluence and linkage with other people.


  • Relationality design including community and communication design
  • Boundary-mediated and/or relationality-oriented systems design
  • Evolutionary multi-agent system and driving agent
  • Evolutionary robotics
  • Genetic programming
  • Human robot/agent interactions