ECE515 Game TheoryIstanbul Okan UniversityDegree Programs Advanced Electronics and Communication Technology (English) with thesisGeneral Information For StudentsDiploma SupplementErasmus Policy StatementNational Qualifications
Advanced Electronics and Communication Technology (English) with thesis
Master TR-NQF-HE: Level 7 QF-EHEA: Second Cycle EQF-LLL: Level 7

General course introduction information

Course Code: ECE515
Course Name: Game Theory
Course Semester: Spring
Course Credits:
Theoretical Practical Credit ECTS
3 0 3 10
Language of instruction: EN
Course Requisites:
Does the Course Require Work Experience?: No
Type of course: Department Elective
Course Level:
Master TR-NQF-HE:7. Master`s Degree QF-EHEA:Second Cycle EQF-LLL:7. Master`s Degree
Mode of Delivery: Face to face
Course Coordinator : Dr.Öğr.Üyesi DİDEM KIVANÇ TÜRELİ
Course Lecturer(s): Prof. Dr. Ufuk Türeli
Prof. Dr. SEZGİN SEZER
Dr.Öğr.Üyesi DİDEM KIVANÇ TÜRELİ
Course Assistants:

Course Objective and Content

Course Objectives: The course gives an introduction to the principles of game theory and mechanism design. It covers equilibria, repeated games, bargaining, and supermodular games. Applications are provided when available.
Course Content: Oyunda denge, tekrarlanan oyunlar, pazarlık ve süper modüler oyunlar. Geriye Dönük Çıkarım, Bayes Oyunları, Potansiyel Oyunlar.

Learning Outcomes

The students who have succeeded in this course;
Learning Outcomes
1 - Knowledge
Theoretical - Conceptual
1) Analyze complex strategic interactions and decision-making processes using game theory frameworks, including Nash equilibrium, extensive form games, and Bayesian games.
2) Apply game theory principles to model and solve engineering problems in various domains such as network optimization, resource allocation, and auction mechanisms.
3) Critically evaluate the implications of different solution concepts and equilibrium refinements in game theory for real-world engineering scenarios, considering factors such as uncertainty, asymmetrical information, and multi-agent interactions.
2 - Skills
Cognitive - Practical
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
Competence to Work Independently and Take Responsibility

Lesson Plan

Week Subject Related Preparation
1) • Games in strategic form and Nash equilibrium • Games in strategic form and iterated strict dominance • Nash equilibrium • Existence and properties of Nash equilibria Read corresponding section in book
2) • Iterated strict dominance and rationalizability o Iterated strict dominance: definition and properties o An application of iterated strict dominance o Rationalizability o Rationalizability and iterated strict dominance • Correlated equilibrium • Rationalizability and subjective correlated equilibria Read corresponding section in book
3) Extensive-form games • Commitment and perfection in multi-stage games with observed actions o Multi-stage games o Backward induction and subgame perfection o The value of commitment and time consistency • The extensive form o Definition of the extensive form o Multi-stage games with observed actions • Strategies and equilibria in extensive-form games o Behavior strategies o The strategic-form representation of extensive-form games o The equivalence between mixed and behavior strategies in games of perfect recall o Iterated strict dominance and Nash equilibrium • Backward induction and subgame perfection • Critiques of backward induction and subgame perfection o Critiques of backward induction o Critiques of subgame perfection Read corresponding section in book
4) Applications of multi-stage games with observed actions • Principle of optimality and subgame perfection • A first look at repeated games • The Rubinstein-Stahl bargaining model o A subgame-perfect equilibrium o Uniqueness of infinite-horizon equilibrium o Comparative statistics • Simple timing games o Definition of simple timing games o The war of attrition o Preemption games • Iterated conditional dominance and the Rubinstein bargaining game • Open-loop and closed-loop equilibria o Definitions of equilibria o A two-period example o Open-loop and closed-loop equilibria in games with many players • Finite-horizon and infinite-horizon equilibria Read corresponding section in book
5) Repeated games • Repeated games with observable actions o The model o The folk theorem for infinitely repeated games o Characterization of the equilibrium set • Finitely repeated games • Repeated games with varying opponents o Repeated games with long-run and short-run players o Games with overlapping generations of players o Randomly matched opponents • Pareto perfection and renegotiation-proofness in repeated games o Introduction to Pareto perfection o Pareto perfection in finitely repeated games o Renegotiation-proofness in infinitely repeated games • Repeated games with imperfect public information o The model o Trigger-price strategies o Public strategies and public equilibria o Dynamic programming and self-generation • The Folk theorem with imperfect public information • Changing the information structure with the time period
6) Bayesian games and Bayesian equilibrium • Incomplete information • Providing a public good under incomplete information • The notions of type and strategy • Bayesian equilibrium • Further examples of Bayesian equilibria • Deletion of strictly dominated strategies o Interim vs. ex ante dominance o Examples of iterated strict dominance • Using Bayesian equilibria to justify mixed equilibria o Examples o Purification theorem • The distributional approach
7) Bayesian games and mechanism design • Examples of mechanism design o Nonlinear pricing o Auctions • Mechanism design and the revelation principle • Mechanism design with a single agent o Implementable decisions and allocations o Optimal mechanisms • Mechanisms with several agents: feasible allocations, budget balance and efficiency o Feasibility under budget balance o Dominant strategy vs. Bayesian mechanisms o Efficiency theorems o Inefficiency theorems o Efficiency limit theorems o Strong inefficiency limit theorems • Mechanism design with several agents: optimization o Auctions o Efficient bargaining processes • Further topics in mechanism design o Correlated types o Risk aversion o Informed principal o Dynamic mechanism design o Common agency
8) Equilibrium refinements: perfect Bayesian equilibrium, sequential equilibrium and trembling-hand perfection • Perfect Bayesian equilibrium in multi-stage games of incomplete information o The basic signaling games o Examples of signaling games o Multi-stage games with observed actions and incomplete information • Extensive-form refinements o Review of game trees o Sequential equilibrium o Properties of sequential equilibrium o Sequential equilibrium compared with perfect Bayesian equilibrium • Strategic-form refinements o Trembling-hand perfect equilibrium Proper equilibrium Read corresponding section in book
9) Reputation Effects • Games with a single long-run player o The chain-store game o Reputation effects with a single long-run player: the general case o Extensive-form stage games • Games with many long-run players o General stage games and general reputations o Common-interest games and bounded-recall reputation • A single big player against many simultaneous long-lived opponents • MIDTERM Preparation for exam
10) Sequential bargaining under incomplete information • Intertemporal price discrimination: the single-sale model o The framework o A two-period introduction to Coasian dynamics o An infinite-horizon example of the Coase conjecture o The skimming property o The gap case o The no-gap case o Gap vs. no gap and extensions of the single-sale model • Intertemporal price discrimination: the rental or repeated-sale model o Short-term contracts o Long-term contracts and renegotiation • Price offers by an informed buyer o One-sided offers and bilateral asymmetric information o Alternating offers and one-sided asymmetric information o Mechanism design and bargaining
11) More equilibrium refinements: stability, forward induction and iterated weak dominance • Strategy stability • Signaling games • Forward induction, iterated weak dominance and burning money • Robust predictions under payoff uncertainty
12) Advanced topics in strategic-form games • Generic properties of Nash equilibria o Number of Nash equilibria o Robustness of equilibria to payoff perturbations • Existence of Nash equilibrium in games with continuous action spaces and discontinuous payoffs o Existence of a pure-strategy equilibrium o Existence of a mixed-strategy equilibrium • Supermodular games
13) Payoff-relevant strategies and Markov equilibrium • Markov equilibria in specific classes of games o Stochastic games: definition and existence of MPE o Separable sequential games o Examples from economics • Markov perfect equilibrium in general games: definition and properties o Definition of Markov perfect equilibrium o Existence o Robustness to payoff perturbations • Differential games o Definition of differential games o Equilibrium conditions o Linear-quadratic differential games o Technical issues o Zero-sum differential games • Capital-accumulation games o Open-loop, closed-loop and Markov strategies o Differential-game strategies
14) Common knowledge and games • Knowledge and common knowledge • Common knowledge and equilibrium o The dirty faces and the Sage o Agreeing to disagree o No-speculation theorems o Interim efficiency and incomplete contracts • Common knowledge, almost common knowledge and the sensitivity of equilibria to the information structure o The lack of lower hemi-continuity o Lower hemi-continuity and almost common knowledge
15) Final Exam None

Sources

Course Notes / Textbooks: Drew Fudenberg and Jean Tirole. Game Theory, 11th Edition. MIT Press, 1991. ISBN:9780262061414.
References: Zhu Han, D. Niyato, W. Saad, T. Başar, Game Theory for Next Generation Wireless and Communication Networks: Modeling, Analysis, and Design
Cambridge University Press 2020.

Course-Program Learning Outcome Relationship

Learning Outcomes

1

2

3

Program Outcomes
1) By carrying out scientific research in their field, graduates evaluate and interpret deeply and broadly, their findings and apply their findings.
2) Graduates have extensive knowledge about current techniques and methods applied in engineering and their limitations.
3) Graduates can complet and implement knowledge using scientific methods using limited or incomplete data; can use the information of different disciplines together.
4) Graduates are aware of new and evolving practices of their profession, examinining new knowledge and learning as necessary
5) Graduates can define and formulate problems related to the field, develop methods to solve them and apply innovative methods in solutions.
6) Graduates develop new and/or original ideas and methods; design complex systems or processes and develop innovative / alternative solutions in their designs.
7) Graduates design and apply theoretical, experimental and model-based research; analyze and investigate the complex problems encountered in this process.
8) Lead in multidisciplinary teams, develop solution approaches in complex situations, work independently and take responsibility.
9) A foreign language communicates verbally and in writing using at least the European Language Portfolio B2 General Level.
10) Transfers the processes and outcomes of their work in a systematic and explicit manner, either written or verbally, in the national or international contexts of that area.
11) Recognize the social, environmental, health, safety, legal aspects of engineering applications, as well as project management and business life practices, and are aware of the limitations they place on engineering applications.
12) Consider social, scientific and ethical values in the collection, interpretation, announcement of data and in all professional activities.

Course - Learning Outcome Relationship

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) By carrying out scientific research in their field, graduates evaluate and interpret deeply and broadly, their findings and apply their findings.
2) Graduates have extensive knowledge about current techniques and methods applied in engineering and their limitations.
3) Graduates can complet and implement knowledge using scientific methods using limited or incomplete data; can use the information of different disciplines together.
4) Graduates are aware of new and evolving practices of their profession, examinining new knowledge and learning as necessary
5) Graduates can define and formulate problems related to the field, develop methods to solve them and apply innovative methods in solutions.
6) Graduates develop new and/or original ideas and methods; design complex systems or processes and develop innovative / alternative solutions in their designs.
7) Graduates design and apply theoretical, experimental and model-based research; analyze and investigate the complex problems encountered in this process.
8) Lead in multidisciplinary teams, develop solution approaches in complex situations, work independently and take responsibility.
9) A foreign language communicates verbally and in writing using at least the European Language Portfolio B2 General Level.
10) Transfers the processes and outcomes of their work in a systematic and explicit manner, either written or verbally, in the national or international contexts of that area.
11) Recognize the social, environmental, health, safety, legal aspects of engineering applications, as well as project management and business life practices, and are aware of the limitations they place on engineering applications.
12) Consider social, scientific and ethical values in the collection, interpretation, announcement of data and in all professional activities.

Learning Activity and Teaching Methods

Lesson
Group study and homework
Reading
Homework

Assessment & Grading Methods and Criteria

Assessment & Grading

Semester Requirements Number of Activities Level of Contribution
Project 1 % 20
Midterms 1 % 30
Final 1 % 50
total % 100
PERCENTAGE OF SEMESTER WORK % 50
PERCENTAGE OF FINAL WORK % 50
total % 100

Workload and ECTS Credit Grading

Activities Number of Activities Duration (Hours) Workload
Course Hours 14 3 42
Project 1 50 50
Midterms 1 50 50
Final 1 60 60
Total Workload 202