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- School of Environment and Society
- 工学院，物質理工学院，環境・社会理工学院共通科目
- Liberal arts and basic science courses
- First-Year Courses
- School of Science
- School of Engineering
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
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School of Environment and Society
- Department of Architecture and Building Engineering
- Department of Civil and Environmental Engineering
- Department of Transdisciplinary Science and Engineering
- Department of Social and Human Sciences
- Department of Innovation Science
- Graduate major in Technology and Innovation Management
- Common courses
- Liberal arts and basic science courses
- Academic unit or major
- Graduate major in Technology and Innovation Management
- Instructor(s)
- Nakamaru Mayuko
- Class Format
- Lecture / Exercise (Blended)
- Media-enhanced courses
- Day/Period(Room No.)
- Sat5-6(CIC)
- Group
- -
- Course number
- TIM.A511
- Credits
- 1
- Academic year
- 2022
- Offered quarter
- 2Q
- Syllabus updated
- 2022/6/9
- Lecture notes updated
- -
- Language used
- Japanese
- Access Index
-
Course description and aims
This course teaches how agent-based simulation helps understand innovation management. The aim of this course is to acquire analytical skills which are required to learn and to conduct research on technology management.
Agent-based simulation is a good tool to grasp the essence of individuals and organizations. In this course, the students will learn and exercise the methodology of agent-based simulation.
Student learning outcomes
In this course, the students will learn:
1) how to grasp the cause-and-effect relationship in innovation management and make a model to describe it qualitatively and quantitatively.
2) how to program and simulate the model.
3) how to interprete the results properly by comparison with practice.
Keywords
agent-based simulation
Competencies that will be developed
| ✔ Specialist skills | Intercultural skills | Communication skills | Critical thinking skills | ✔ Practical and/or problem-solving skills |
Class flow
Give a lecture and then exercises are assigned to students.
Course schedule/Required learning
| Course schedule | Required learning | |
|---|---|---|
| Class 1 | Introduction: what agent-based simulation is? Lecture and exercise: Schelling’s dynamic model of segregation | learn what agent-based simulation is learn and exercise Schelling’s dynamic model of segregation |
| Class 2 | Exercise in Schelling’s dynamic model of segregation | learn and exercise Schelling’s dynamic model of segregation |
| Class 3 | Lecture and exercise: Evolution of cooperation in a lattice | learn and exercise the evolution of cooperation in a lattice |
| Class 4 | Lecture and exercise: Evolution of indirect reciprocity | learn and exercise the evolution of cooperation in a lattice |
| Class 5 | Exercise in Dissemination of Culture in a lattice and Opinion dynamics | learn and exercise Dissemination of Culture in a lattice and Opinion dynamics |
| Class 6 | Group discussion | Students join one of groups and then discuss what model is made |
| Class 7 | Group presentation | Students present their assignment. |
Out-of-Class Study Time (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)
Not assigned.
Reference books, course materials, etc.
Not assigned.
Assessment criteria and methods
Report (100%)
Related courses
- TIM.A510 ： Social Simulation I
- TIM.A414 ： Introduction to Models and Experiments in Social Science
- TIM.C401 ： Ecosystem Management I
- TIM.C402 ： Ecosystem Management II
- TIM.D401 ： Exercises in Research Literacy I
- TIM.D402 ： Exercises in Research Literacy II
Prerequisites (i.e., required knowledge, skills, courses, etc.)
Take Social Simulation I
