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252-1407-00L 7 Credits DZ , SHE , MSC , WBZ D-ITET , D-INFK , D-MATH
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Algorithmic Game Theory

Lecturers & Examiners: Dr. Paolo Penna
VVZ CR n/a

Last Updated: 2026-02-05 15:35:55

Abstract

Game theory provides a formal model to study the behavior and interaction of self-interested users and programs in large-scale distributed computer systems without central control. The course discusses algorithmic aspects of game theory.

Objective

Learning the basic concepts of game theory and mechanism design, acquiring the computational paradigm of self-interested agents, and using these concepts in the computational and algorithmic setting.

Content

The Internet is a typical example of a large-scale distributed computer system without central control, with users that are typically only interested in their own good. For instance, they are interested in getting high bandwidth for themselves, but don't care about others, and the same is true for computational load or download rates. Game theory provides a mathematical model for the behavior and interaction of such selfish users and programs. Classic game theory dates back to the 1930s and typically does not consider algorithmic aspects at all. Only a few years back, algorithms and game theory have been considered together, in an attempt to reconcile selfish behavior of independent agents with the common good. This course discusses algorithmic aspects of game-theoretic models, with a focus on recent algorithmic and mathematical developments. Rather than giving an overview of such developments, the course aims to study selected important topics in depth. Outline: - Introduction to classic game-theoretic concepts. - Existence of stable solutions (equilibria), algorithms for computing equilibria, computational complexity. - Speed of convergence of natural game playing dynamics such as best-response dynamics or regret minimization. - Techniques for bounding the quality-loss due to selfish behavior versus optimal outcomes under central control (a.k.a. the 'Price of Anarchy'). - Design and analysis of mechanisms that induce truthful behavior or near-optimal outcomes at equilibrium. - Selected current research topics, such as Google's Sponsored Search Auction, the U.S. FCC Spectrum Auction, Kidney Exchange.

Resources

Lecture Notes

Lecture notes will be usually posted on the website shortly after each lecture.

Literature

"Algorithmic Game Theory", edited by N. Nisan, T. Roughgarden, E. Tardos, and V. Vazirani, Cambridge University Press, 2008; "Game Theory and Strategy", Philip D. Straffin, The Mathematical Association of America, 5th printing, 2004 Several copies of both books are available in the Computer Science library.

Learning Materials (Links)

General Information

Language
English
Levels
DZ , SHE , MSC , WBZ
Frequency
Yearly recurring

Examination

Type
session examination
Mode
written 180 minutes
Aids
no supporting material allowed
There will be 4 exercise sheets (compulsory continuous performance assessments) and the best 3 of them will determine your "excercise grade". The total final grade will be a combination of your exercise grade (30%) and your exam grade (70%).

Course Components

Type Title Time & Place Hours
lecture Algorithmic Game Theory
  • Mon 10:15-13:00 (CAB G 61)
3 h weekly
exercise Algorithmic Game Theory
Students will be assigned to groups at the beginning of the semester.
  • Tue 10:15-12:00 (CAB G 56)
  • Tue 10:15-12:00 (CAB G 57)
  • Tue 16:15-18:00 (LFW B 3)
2 h weekly
independent project Algorithmic Game Theory
Project Work, no fixed presence required.
No time listed 1 h weekly

Offered In