Multiagent Systems (CMPE562) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Multiagent Systems CMPE562 Elective Courses 3 0 0 3 5
Pre-requisite Course(s)
N/A
Course Language English
Course Type Elective Courses
Course Level Natural & Applied Sciences Master's Degree
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives The objective of this course is to introduce the concepts of agent and multi-agent systems and their applications and the basic design issues related to agent and multi-agent systems.
Course Learning Outcomes The students who succeeded in this course;
  • Explain the agent notion, the difference between agent and other software paradigms
  • Review approaches for developing agents
  • Comprehend how agent societies communicate, cooperate, negotiate and coordinate for solving problems
  • Design and develop multi-agent systems
Course Content Agent paradigm, abstract agent architectures, design of intelligent agents, agent cooperation, auction systems, negotiation, argumentation, interaction languages and protocols, distributed problem solving, coordination, applications for multi-agent systems.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Introduction Chapters 1 (main text)
2 Intelligent Agents Chapter 2
3 Intelligent Agents Chapter 2
4 Deductive Reasoning Agents Chapter 3
5 Practical Reasoning Agents Chapter 4
6 Reactive and Hybrid Agents Chapter 5
7 Multiagent Interactions Chapter 6
8 Multiagent Interactions Chapter 6
9 Reaching Agreements Chapter 7
10 Reaching Agreements Chapter 7
11 Communication Chapter 8
12 Working Together Chapter 9
13 Methodologies Chapter 10
14 Applications Chapter 11
15 Review
16 Review

Sources

Course Book 1. An Introduction to MultiAgent Systems, Wooldridge, M., John Wiley & Sons, 2002, ISBN: 047149691X.
Other Sources 2. G.Weiss, Multi-Agent Systems, The MIT Press, 1999.
3. Readings in Agents, Singh, M. and Huhns, M., Morgan-Kaufmann Publishers, 1997.
4. Ferber, J., Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence, Ferber, J., Addison-Wesley, 1999, ISBN: 0-201-36048-9
5. Shoham, Y. and Leyton-Brown, Kevin, Multiagent Systems: Algorithmic, Game–Theoretic and Logical Foundations, Cambridge University Press, 2009.
6. Shoham, Y. and Leyton-Brown, Kevin, Essentials of Game Theory, Morgan and Claypool, 2008.

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments - -
Presentation 1 10
Project 1 20
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 25
Final Exam/Final Jury 1 45
Toplam 4 100
Percentage of Semester Work 55
Percentage of Final Work 45
Total 100

Course Category

Core Courses
Major Area Courses X
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 An ability to apply knowledge of mathematics, science, and engineering. X
2 An ability to design and conduct experiments, as well as to analyse and interpret data.
3 An ability to design a system, component, or process to meet desired needs. X
4 An ability to function on multi-disciplinary domains.
5 An ability to identify, formulate, and solve engineering problems. X
6 An understanding of professional and ethical responsibility. X
7 An ability to communicate effectively. X
8 Recognition of the need for, and an ability to engage in life-long learning. X
9 A knowledge of contemporary issues. X
10 An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice. X
11 Skills in project management and recognition of international standards and methodologies X
12 An ability to produce engineering products or prototypes that solve real-life problems. X
13 Skills that contribute to professional knowledge. X
14 An ability to make methodological scientific research. X
15 An ability to produce, report and present an original or known scientific body of knowledge. X
16 An ability to defend an originally produced idea.

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 16 2 32
Presentation/Seminar Prepration 1 7 7
Project 1 10 10
Report
Homework Assignments
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 1 10 10
Prepration of Final Exams/Final Jury 1 20 20
Total Workload 127