Social Simulation /Exercise1

The main aims of this course are to deeply understand the theory and practice of social simulation as an effective decision-making support method in today's highly uncertain society. Specifically, this course helps students achieve the following three objectives: 1) Acquire modeling methods to capture the complexity of social systems. 2) Develop specific simulation techniques based on data analysis. 3) Examine practical methodologies for applying these techniques to policy-making and problem-solving in the real world.

Social simulation, which deepens the understanding of target systems through modeling and simulation for complex social system problems, has been attracting attention in recent years as an effective decision-making support method under highly uncertain conditions, and has begun to contribute to policy-making in the real world. However, there is still room for development in modeling and simulation technologies for social systems, and research for the practical use of social simulation is strongly requested by society. This course deals with a wide range of themes in the field of social simulation, focusing on data analysis for modeling social systems, simulation technology, and practical methodologies.

1. Obtain specialized knowledge regarding data analysis, simulation technology, and practical methodologies for modeling social systems.
2. Formulate and execute a research plan concerning data analysis, simulation technology, and practical methodologies for modeling social systems.
3. Think logically and communicate their ideas effectively during research presentations and discussions.

Japanese(English accepted)

Students will select a research theme from a wide range of topics in the field of social simulation, focusing on data analysis for social system modeling, simulation technology, and practical methodologies. Based on the selected theme, students are expected to conduct a literature review of related research, perform data analysis, and integrate the results of their modeling and simulation into a presentation for class discussion.

Your overall grade in the class will be decided based on the following:
1) Surveys, Presentations, and Discussions on the selected theme: 50%
2) Research Planning, Execution, and Reporting: 50%

To pass, students must earn at least 60 points out of 100.
Extra points will be awarded for presenting at domestic or international academic conferences/workshops, or participating in various competitions. These additional points will be reflected in the final grade based on an evaluation of the content.

Reference Book:
- Shingo Takahashi, Yusuke Goto, and Kotaro Ohori, Social System Modeling, Kyoritsu Shuppan (2022)
- Michael C. Jackson, Systems Thinking: Creative Holism for Managers. Wiley (2003)
- Michael J. North, Charles M. Macal, Managing Business Complexity: Discovering Strategic Solutions with Agent-Based Modeling and Simulation. Oxford University Press (2007)

Students are expected to meet the following requirements before taking this course:
- Programming Skills: Understand the basic syntax of the Python programming language and be able to develop small-scale programs.
- Analytical Experience: Have prior experience in either data analysis or simulation analysis.

• Questions and consultations are accepted at any time via Slack.
  In addition, individual meetings can be arranged at a convenient time by making an appointment in advance.

Non-regionally-oriented course

• Course that cultivates an ability for utilizing knowledge
• Course that cultivates a basic interpersonal skills
• Course that cultivates a basic self-management skills
• Course that cultivates a basic problem-solving skills

Most classes are interactive

• 4.QUALITY EDUCATION
• 8.DECENT WORK AND ECONOMIC GROWTH
• 9.INDUSTRY, INNOVATION AND INFRASTRUCTURE
• 10.REDUCED INEQUALITIES
• 11.SUSTAINABLE CITIES AND COMMUNITIES