Algorithmic Game Theory and Mechanism Design
2nd Semester, Course Code: ΜΕΧΤΕ203
Credits: 7,5
Learning Outcomes
Algorithmic Game Theory is an interdisciplinary field that combines concepts from computer science, economics, and mathematics to analyse strategic interactions in computational settings. This graduate course provides a comprehensive introduction to the fundamental theories, techniques, and applications of Algorithmic Game Theory. Students will gain a deep understanding of strategic decision-making, game-theoretic models, algorithm design, and computational complexity in the context of economic and social systems.
The course objectives are:
- understand the basic concepts of game theory and their applications,
- explore the equilibrium concepts and their computational aspects
- investigate the complexity of computing equilibria in various game-theoretic models and
- examine the role of mechanism design in optimizing outcomes and incentivizing strategic behaviour.
General Competences
- Decision-Making
- Production of new research ideas
- Working in an interdisciplinary environment
Course Content
- Games in normal form, Pareto optimality, Nash equilibrium
- Games in normal form, Refinements, Bayesian Games
- Equilibrium computation in normal form games, the Lemke-Howson algorithm
- Games with sequential actions, the Perfect information extensive form
- The basics of mechanism design., Introduction and examples
- Auctions, single-item auctions, sealed-bid auctions, first and second price auctions
- The Myerson lemma,, single-parameter environments, allocation and payment rules, statement of the lemma and proof
- The VCG mechanism, multi-parameter environments, the Revelation principle
- Matching theory, one-to-one matching, stable matching, many-to-one matching Gale-Shapley algorithm
- Overview of the material, more examples and exercises. Presentations
Student Performance Evaluation
- Final exam 60%
- Problem solving 20%
- Public presentation 20%
Bibliography
Suggested Bibliography
- Roughgarden, Tim.Twenty lectures on algorithmic game theory. Cambridge University Press, 2016.
- Vlassis, Nikos.A concise introduction to multiagent systems and distributed artificial intelligence. Springer Nature, 2022.
- Βολιώτης Δημήτρης, Διαλέξεις στην θεωρία παιγνίων, Εκδόσεις Πεδίο 2015
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