lidya multisite > Computer Engineering Department > CENG 568

About

CENG 568

Multiagent Systems

Course Information
CENG568

 

 Multiagent Systems
Course Semester T+A Credits ECTS Credits
3+0 3 9
Course Language English
Course Level Graduate
Department/Program Computer Engineering/Master of Science
Mode of delivery Face to face
Course Type Compulsory [ ] / Technical Elective [ X ]
Course Objectives To advance students on the current trends in multiagent systems.

 
Course Content Intelligent agents, deductive reasoning, practical reasoning and reactive and hybrid agents, multiagent interactions, communication, cooperative distributed problem solving
Course Prerequisites  

None
Course Coordinator  Asst. Prof. Dr. Emrah İnan
Course Lecturer(s)  Asst. Prof. Dr. Emrah İnan
Course Assistants None
Course Internship None
Course Resources
Resources Michael Wooldridge, An Introduction to Multiagent Systems, John wiley & sons, 2009.

 

Y.Shoham and K. Leyton-Brown, Multiagent Systems: Algorithmic, Game-Theoretic and Logical Foundations, Cambridge University Press, 2009.

 
Planned Learning Activities and Teaching Methods
 Presentation, homework, research.
Assessment Criteria ECTS Workload Calculation
In-term Studies Quantity Percentage% Activities Quantity Duration Workload (Hour)
Home works 2 20% Weekly course 14 3 42
Cases – Outside Activities About Course (Homework, Reading, Individual studies etc.) 14 2 28
Laboratory works –
Other activities –
Projects –
Quizzes – Exams and Exam Preparations (Attendance, Presentation, Midterm

exam, Final exam, Quiz etc.)

 2 5 10
Midterm exams 1 35%
Final examination 1 45%
Total Total Workload 80
Course Learning Outcomes
The students who succeeded in this course will be able to:
No Explanation
1 To be able to understand the fundamental concepts of intelligent agents and their types, including deductive, practical, and reactive agents.
2 To be able to analyze multiagent interactions and their role in reaching agreements, communication, and cooperative distributed problem-solving.
3 To be able to apply logics for multiagent systems to model and reason about agent behavior in complex environments.
4 To be able to explore the applications of intelligent agents, with a focus on their use in large language models.
Weekly Course Plan
Week Topics
1  Introduction
2  Intelligent agents
3  Deductive reasoning agents
4  Practical reasoning agents
5  Reactive and hybrid agents
6  Multiagent interactions
7  Reaching Agreements
8  Communication
9  Cooperative distributed problem solving
10  Methodologies
11  Logics for multiagent systems
12  Applications
13  Applications in large language models
14  Discussion

Instructor(s)

Assistant Professor / Vice Chair
Emrah İnan
Other MS Courses