CENG0054 Multi-agent Systems

6 ECTS - 3-0 Duration (T+A)- . Semester- 3 National Credit

Information

Code CENG0054
Name Multi-agent Systems
Term 2024-2025 Academic Year
Semester . Semester
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 6 ECTS
National Credit 3 National Credit
Teaching Language Türkçe
Level Yüksek Lisans Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Mehmet SARIGÜL


Course Goal / Objective

The goal of a multi-agent systems course is to introduce students to the concepts and techniques used in the design and analysis of systems that involve multiple interacting agents. Multi-agent systems are systems that consist of multiple autonomous entities, each with its own goals, beliefs, and capabilities, that interact with each other to achieve individual and collective objectives.

Course Content

This course covers Normal Form Games, Normal Form Definitions, Dominant Strategies, Pareto Optimality, Mixed Strategies and Nash Equilibrium. Maxmin Strategy, Minimax regret, Iterative Removal of Dominant Strategies, Computing Nash Equilibrium, Complexity of Nash Equilibrium and Compact Representation. Extensive Form Definitions, Centipede Game, Backward Inductions, Inperfect Information, and Subgame Perfect Equilibrium, Finite Repetitive Games, Infinitely Repetitive Games, Stochastic Games, Learning in Repetitive Games, Folk Theorems. Coalitionary Game Theory, Shapley Value, Nucleus and Bayes Games. Rational Learning, Reinforcement Learning, Replicator Dynamics and Evolutionarily Stable Strategies, and Congestion Games.

Course Precondition

Knowledge of basic programming, linear algebra, and probability theory.

Resources

Shoham, Yoav, and Kevin Leyton-Brown. Multiagent systems: Algorithmic, game-theoretic, and logical foundations. Cambridge University Press, 2008.

Notes

Shoham, Yoav, and Kevin Leyton-Brown. Multiagent systems: Algorithmic, game-theoretic, and logical foundations. Cambridge University Press, 2008.


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Understanding of the fundamental concepts of multi-agent systems
LO02 Familiarity with different approaches to modeling and analyzing multi-agent systems
LO03 Ability to design and implement multi-agent systems
LO04 Ability to analyze the performance of multi-agent systems


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal On the basis of the competencies gained at the undergraduate level, it has an advanced level of knowledge and understanding that provides the basis for original studies in the field of Computer Engineering. 2
PLO02 Bilgi - Kuramsal, Olgusal By reaching scientific knowledge in the field of engineering, he/she reaches the knowledge in depth and depth, evaluates, interprets and applies the information. 3
PLO03 Yetkinlikler - Öğrenme Yetkinliği Being aware of the new and developing practices of his / her profession and examining and learning when necessary. 3
PLO04 Yetkinlikler - Öğrenme Yetkinliği Constructs engineering problems, develops methods to solve them and applies innovative methods in solutions. 3
PLO05 Yetkinlikler - Öğrenme Yetkinliği Designs and applies analytical, modeling and experimental based researches, analyzes and interprets complex situations encountered in this process. 2
PLO06 Yetkinlikler - Öğrenme Yetkinliği Develops new and / or original ideas and methods, develops innovative solutions in system, part or process design. 3
PLO07 Beceriler - Bilişsel, Uygulamalı Has the skills of learning. 2
PLO08 Beceriler - Bilişsel, Uygulamalı Being aware of new and emerging applications of Computer Engineering examines and learns them if necessary. 3
PLO09 Beceriler - Bilişsel, Uygulamalı Transmits the processes and results of their studies in written or oral form in the national and international environments outside or outside the field of Computer Engineering.
PLO10 Beceriler - Bilişsel, Uygulamalı Has comprehensive knowledge about current techniques and methods and their limitations in Computer Engineering. 1
PLO11 Beceriler - Bilişsel, Uygulamalı Uses information and communication technologies at an advanced level interactively with computer software required by Computer Engineering. 2
PLO12 Bilgi - Kuramsal, Olgusal Observes social, scientific and ethical values in all professional activities. 2


Week Plan

Week Topic Preparation Methods
1 Introduction to multi-agent systems, agents and environments Reading the lecture notes Öğretim Yöntemleri:
Anlatım
2 Coordination and cooperation among agents Reading the lecture notes Öğretim Yöntemleri:
Anlatım
3 Game theory for multi-agent systems Reading the lecture notes Öğretim Yöntemleri:
Anlatım
4 Distributed decision-making and consensus protocols Reading the lecture notes Öğretim Yöntemleri:
Anlatım
5 Multi-agent learning and reinforcement learning Reading the lecture notes Öğretim Yöntemleri:
Anlatım
6 Communication among agents and message-passing algorithms Reading the lecture notes Öğretim Yöntemleri:
Anlatım
7 Auctions and mechanism design Reading the lecture notes Öğretim Yöntemleri:
Anlatım
8 Mid-Term Exam Ölçme Yöntemleri:
Yazılı Sınav
9 Swarm intelligence and collective behavior Reading the lecture notes Öğretim Yöntemleri:
Anlatım
10 Multi-robot systems and coordination Reading the lecture notes Öğretim Yöntemleri:
Anlatım
11 Multi-agent pathfinding and planning Reading the lecture notes Öğretim Yöntemleri:
Anlatım
12 Privacy and security in multi-agent systems Reading the lecture notes Öğretim Yöntemleri:
Anlatım
13 Human-agent interaction and explainable AI Reading the lecture notes Öğretim Yöntemleri:
Anlatım
14 Applications of multi-agent systems in smart cities Reading the lecture notes Öğretim Yöntemleri:
Anlatım
15 Review Reading the lecture notes Öğretim Yöntemleri:
Anlatım
16 Term Exams Ölçme Yöntemleri:
Yazılı Sınav
17 Term Exams Ölçme Yöntemleri:
Yazılı Sınav


Student Workload - ECTS

Works Number Time (Hour) Workload (Hour)
Course Related Works
Class Time (Exam weeks are excluded) 14 3 42
Out of Class Study (Preliminary Work, Practice) 14 5 70
Assesment Related Works
Homeworks, Projects, Others 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 14 14
Final Exam 1 28 28
Total Workload (Hour) 154
Total Workload / 25 (h) 6,16
ECTS 6 ECTS

Update Time: 13.05.2024 03:07