2024 Faculty Courses Liberal arts and basic science courses Humanities and social science courses
Social Modeling C
- Academic unit or major
- Humanities and social science courses
- Instructor(s)
- Kotaro Ohori / Hirokazu Anai / Hiroaki Iwashita
- Class Format
- Lecture (Face-to-face)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 3-4 Mon / 3-4 Thu
- Class
- -
- Course Code
- LAH.T308
- Number of credits
- 200
- Course offered
- 2024
- Offered quarter
- 2Q
- Syllabus updated
- Mar 14, 2025
- Language
- Japanese
Syllabus
Course overview and goals
This course deals with basic methodologies for understanding and solving complex social issues. Specially, this course takes up some mathematical technologies to appropriately take into account human behavior and psychology such as game theory, mechanism design, network analysis, agent-based social simulation, and useful artificial intelligence (AI) technologies for developing social solutions.
This course aims to cultivate the students' abilities to understand the process of social system design consisting of social system modeling, policies and programs design and their evaluation.
Course description and aims
Upon completion of this course, students should be able to:
1） State the basic concepts utilized in some theories related to social system design,
2） Model, analyze and design mathematically some situations of an issue in social systems,
3） State a set of processes for social system design.
Student learning outcomes
実務経験と講義内容との関連 (又は実践的教育内容)
Instructors have practically solved real social problems using mathematical technologies.
This course includes some case studies on the problem solving processes.
Keywords
systems approach, artificial intelligence, game theory, mechanism design, network analysis, agent-based social simulation, optimization
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
Each theme is dealt with over a set of classes (one set : 1 to 3 classes)
Students work on exercise problems during a class. At the end of the class, each student writes and submits a "exercise report" on what he/she learned through a lecture and exercise problems.
Should the number of applicants for this course exceed the limit, a lottery system will be used to determine which students are admitted. Be sure to attend the first class.
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | Guidance, briefing | Have a panoramic view of this course |
| Class 2 | Way of thinking on social systems | State the basic concepts of social systems |
| Class 3 | Description of decision making situations 1 | State the role of game theory |
| Class 4 | Description of decision making situations 2 | State how we model decision making situations |
| Class 5 | Applications of artificial intelligence 1 | Understand AI applications based on game theory |
| Class 6 | Social network analysis 1 | State basic concepts of graph theory for describing social networks |
| Class 7 | Social network analysis 2 | State the definition of complex networks and their properties |
| Class 8 | Applications of artificial intelligence 2 | Understand AI applications based on decision making models |
| Class 9 | Policy and program design of social systems 1 | State the role of mechanism design |
| Class 10 | Policy and program design of social systems 2 | Understand and state application examples of mechanism design |
| Class 11 | Applications of artificial intelligence 3 | Understand AI applications to analyze social networks |
| Class 12 | Policy and program evaluation of social systems 1 | State the role of agent-based social simulation |
| Class 13 | Policy and program evaluation of social systems 2 | State the method to analyze simulation results |
| Class 14 | Final examination | Achieve a passing score |
Study advice (preparation and review)
To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.
Textbook(s)
None required.
Reference books, course materials, etc.
Takehiro Inohara, “Rationality and Flexibility,” Keiso-syobo, 2002 (in Japanese)
Takehiro Inohara, “Emotions and Perception,” Keiso-syobo, 2002 (in Japanese)
Shingo Takahashi, “Fundamentals of system science”, Baifukan, 2007 (in Japanese)
Makoto Yokoo, “Fundamentals of auction theory ”, TDU-syuppannkyoku, (in Japanese)
Naoki Masuda, Norio Konno, “Introduction of complex network”, Sangyou-Tosho, 2005 (in Japanese)
Hirokazu Anai, Tsutomu Saito, “Guide book of Combinatorial optimization”, Kodansha, 2015 (in Japanese)
Shingo Takahashi, Yusuke Goto, Kotaro Ohori, “Modeling Social Systems“, Kyoritsu Shuppan, 2022 (in Japanese)
Evaluation methods and criteria
Assessment will be based on “exercise reports” written during each class (20% in total) and the final examination (80%).
Related courses
- LAH.T108 ： Decision Making A
- LAH.T208 ： Decision Making B
- LAH.T307 ： Decision Making C
- LAH.T107 ： Social Modeling A
- LAH.T209 ： Social Modeling B
Prerequisites
None required
Contact information (e-mail and phone) Notice : Please replace from ”[at]” to ”@”(half-width character).
Kotaro Ohori, ohori.k.aa[at]m.titech.ac.jp
Other
We want students to know that there are a variety of mathematical approaches to help solve social issues.
This course includes the content of science.
Should the number of applicants for this course exceed the limit, a lottery system will be used to determine which students are admitted. Be sure to attend the first class.