| Academic Year |
2025Year |
School/Graduate School |
Graduate School of Advanced Science and Engineering (Master's Course) Division of Advanced Science and Engineering Informatics and Data Science Program |
| Lecture Code |
WSN22701 |
Subject Classification |
Specialized Education |
| Subject Name |
Control of multi-agent systems |
Subject Name
（Katakana） |
コントロールオブマルチエージェントシステムズ |
Subject Name in
English |
Control of multi-agent systems |
| Instructor |
NAGAHARA MASAAKI |
Instructor
(Katakana) |
ナガハラ マサアキ |
| Campus |
Higashi-Hiroshima |
Semester/Term |
1st-Year, Second Semester, 3Term |
| Days, Periods, and Classrooms |
(3T) Tues5-8 |
| Lesson Style |
Lecture/Seminar |
Lesson Style
(More Details) |
Face-to-face |
| |
| Credits |
2.0 |
Class Hours/Week |
4 |
Language of Instruction |
B
:
Japanese／English |
| Course Level |
2
:
Undergraduate Low-Intermediate
|
| Course Area（Area） |
25
:
Science and Technology |
| Course Area（Discipline） |
02
:
Information Science |
| Eligible Students |
|
| Keywords |
Multi-agent systems, networks, graph theory, distributed control, distributed optimization. |
| Special Subject for Teacher Education |
|
Special Subject |
|
Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students) | |
|---|
Criterion referenced
Evaluation
(Applicable only to targeted subjects for undergraduate students) | |
|---|
Class Objectives
/Class Outline |
This course will cover the fundamentals of multi-agent system control, a technology used for the distributed and cooperative control of multiple drones and robots. The course will be conducted in a reading seminar format using a textbook written in English. |
| Class Schedule |
lesson1: Introduction to Multi-agent Systems
lesson2: Linear Algebra and Graph Theory (1): Linear Algebra Calculations with Python
lesson3: Linear Algebra and Graph Theory (2): Matrix Eigenvalue Problems
lesson4: Linear Algebra and Graph Theory (3): Fundamentals of Algebraic Graph Theory
lesson5: Consensus Control (1): Continuous-Time Systems
lesson6: Consensus Control (2): Discrete-Time Systems
lesson7: Consensus Control (3): Python Exercises
lesson8: Coverage Control (1): Formulation of Coverage Control
lesson9: Coverage Control (2): Analysis with Gradient Systems
lesson10: Distributed Optimization (1): Fundamentals of Convex Optimization
lesson11: Distributed Optimization (2): Gradient Descent Method
lesson12: Distributed Optimization (3): Proximal Algorithms
lesson13: Distributed Optimization (4): Decentralization of Optimization Problems
lesson14: Distributed Optimization (5): Python Exercises
lesson15: Comprehensive Discussion
A report examination will be conducted. |
Text/Reference
Books,etc. |
M. Nagahara, S. Azuma, and H. Ahn, Control of Multi-agent Systems: Theory and Simulations with Python, Springer, 2024. |
PC or AV used in
Class,etc. |
Text, Handouts |
| (More Details) |
|
| Learning techniques to be incorporated |
|
Suggestions on
Preparation and
Review |
Please read the textbook thoroughly and prepare for the lectures. As this is a reading seminar, please pay particular attention to the sections you are assigned. |
| Requirements |
|
| Grading Method |
Grades will be evaluated based on reading seminar presentations and reports. |
| Practical Experience |
|
| Summary of Practical Experience and Class Contents based on it |
|
| Message |
|
| Other |
|
Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching. |