MA-INF 1301: Algorithmic Game Theory

Please find further details in the eCampus course.

Lecture

When Where Start Lecturer
Two lectures per week online, prerecorded October 11 Kesselheim

Q&A - Session

When Where Start Lecturer
Wednesday, 12:15-12:45 online October 11 Kesselheim

Tutorials

When Where Start Lecturer
Thursday, 10:15-11:45 Meckenheimer Allee 176, Lecture Hall IV October 14 Braun
Thursday, 14:15-15:45 online October 14 Braun

Content

Throughout the world of modern computer networks, there are environments in which participants act strategically. Just consider internet service providers, which strive to route packets as cheaply as possible. Another example are cloud-based services: End-users and service providers rent remote infrastructure for storage or computations, giving rise to huge markets. Last but not least, advertisers want to reach their audience as cheaply as possible. This is the foundation of the business models of the world’s largest companies.

In all these settings, algorithms either act as selfish agents or have to cope with such. This brings about novel questions that are out of the scope of traditional algorithmic theory. Algorithmic game theory, a research direction at the intersection of game theory and algorithm design, has emerged to provide answers. On the one hand, this means to take analytical point of view and to strive to explain the performance of a given system. On the other hand, one also takes engineering perspective, asking how to design systems so that they can cope with selfishly acting agents.

In this course, we will introduce you to the foundations of algorithmic game theory, including

  • basic game theory,
  • computability and hardness of equilibria,
  • convergence of dynamics of selfish agents,
  • (bounds on the) loss of performance due to selfish behavior,
  • designing incentive-compatible auctions
  • maximizing revenue, and
  • designing mechanisms for stable and fair allocations without money.

Prerequisites

You should bring a solid background in algorithms and calculus. No prior knowledge on game theory is required. Specialized knowledge about certain algorithms is not necessary.

Problem Sets - Tutorials

Problem Sets - Homework

Further Reading


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