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Curricular information is subject to change
On successful completion of this module, students should have:
1-An understanding of basic game theory concepts;
2-An ability to apply these tools to various real life and economic settings.
Week 1: Basic concepts of game theory
Weeks 1-2: Simultaneous move games with pure strategies
- Constructing payoffs matrices
- Identify equilibria (Best response analysis, Dominance)
- Particular classes of games (constant-sum games, prisoner’s dilemma games, coordination games)
Weeks 3-4: Sequential Games
- Definitions and game tree representation
- Solving games (sub-game perfect NE)
- From game tree to matrix payoff: NE vs SPNE
- Games with more than 2 players
- Order of moves: first/second mover advantage
- Stage games
Week 5-6: Simultaneous move games with mixed strategies
- Evolutionary game theory
Week 7: Strategic games
Week 8: Repeated games
Week 9: Static Bayesian Games
Week 10: Dynamic Bayesian Games
Weeks 11 - 12 Adverse selection, Signalling and Screening
Student Effort Type | Hours |
---|---|
Autonomous Student Learning | 80 |
Lectures | 22 |
Tutorial | 11 |
Total | 113 |
Students are recommended to have some knowledge of basic Principles of Microeconomics.
Description | Timing | Component Scale | % of Final Grade | ||
---|---|---|---|---|---|
Examination: End of Semester Exam | 2 hour End of Trimester Exam | No | Alternative linear conversion grade scale 40% | No | 70 |
Class Test: MCQ | Week 8 | n/a | Alternative linear conversion grade scale 40% | No | 30 |
Resit In | Terminal Exam |
---|---|
Autumn | No |
• Group/class feedback, post-assessment
• Online automated feedback
• Self-assessment activities
1. Regular problem sets will be assigned throughout the semester for self-assessment; solutions will be posted on Brightspace and will be explained in detail during tutorials. 2. Solutions to midterm examination will be posted on Brightspace within 20 working days from the date of the midterm, and those students who wish to go over their midterm will be given an appointment for individual feedback.
Name | Role |
---|---|
Manuel Estevo Lago Rodríguez | Tutor |