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- School of Life Science and Technology
- 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
- Media-enhanced courses
- Day/Period(Room No.)
- Sat1-2(CIC812)
- Group
- -
- Course number
- TIM.A511
- Credits
- 1
- Academic year
- 2018
- Offered quarter
- 2Q
- Syllabus updated
- 2018/4/5
- 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? | learn what agent-based simulation is |
| Class 2 | Lecture and exercise: Schelling’s dynamic model of segregation | learn and exercise Schelling’s dynamic model of segregation |
| Class 3 | Exercise in Schelling’s dynamic model of segregation | learn and exercise Schelling’s dynamic model of segregation |
| Class 4 | Exercise in Schelling’s dynamic model of segregation | learn and exercise the evolution of cooperation in a lattice (Nowa and May model (1992)) |
| Class 5 | Lecture and exercise: Evolution of cooperation in a lattice | learn and exercise the evolution of cooperation in a lattice (Nowa and May model (1992)) |
| Class 6 | Exercise in Dissemination of Culture in a lattice | learn and exercise Dissemination of Culture in a lattice (Axelrod (1997)) |
| Class 7 | Exercise in Dissemination of Culture in a lattice | learn and exercise Dissemination of Culture in a lattice (Axelrod (1997)) |
| Class 8 | group discussion | discuss the models the students learned here from the viewpoint of management of technology |
Textbook(s)
Not assigned.
Reference books, course materials, etc.
Not assigned.
Assessment criteria and methods
Report (100%)
Related courses
- TIM.A405 ： Methodology of Mathmatical and Computational Analysis I
- TIM.A406
- TIM.C401 ： Ecosystem Management I
- TIM.C402 ： Ecosystem Management II
- TIM.D401 ： Exercises in Research Literacy I
- TIM.D402 ： Exercises in Research Literacy II
- TIM.A510 ： Social Simulation I
Prerequisites (i.e., required knowledge, skills, courses, etc.)
Take Social Simulation I
