Multiagent Systems (CMPE562) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Multiagent Systems CMPE562 Area Elective 3 0 0 3 5
Pre-requisite Course(s)
N/A
Course Language English
Course Type Elective Courses
Course Level Ph.D.
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 X
Major Area Courses
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 Ability to carry out advanced research activities, both individual and as a member of a team
2 Ability to evaluate research topics and comment with scientific reasoning
3 Ability to initiate and create new methodologies, implement them on novel research areas and topics
4 Ability to produce experimental and/or analytical data in systematic manner, discuss and evaluate data to lead scintific conclusions
5 Ability to apply scientific philosophy on analysis, modelling and design of engineering systems
6 Ability to synthesis available knowledge on his/her domain to initiate, to carry, complete and present novel research at international level
7 Contribute scientific and technological advancements on engineering domain of his/her interest area
8 Contribute industrial and scientific advancements to improve the society through research activities

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