Please find further details in the eCampus course.

The exams will be oral and about 25-30 minutes long and they will take place in the Computer Science building. You will need to identify yourself. So please do not forget to bring your ID documents.

The second exam period will take place on August 29 and 30. Please contact Anna Heuser aheuser1@uni-bonn.de by August 21 to be assigned a time slot. Immediately (within a day or two), you will receive a confirmation of the day of your exam; however, we will announce the exact time only a few days before the exam.

One more thing: If you have been assigned a time slot but then decide to not take the exam, please remember to cancel it as soon as possible. It is very important for us to know that you will not show up because otherwise we will be waiting for you. In this case, send an e-mail to aheuser1@uni-bonn.de or thomas.kesselheim@uni-bonn.de. Even a last-minute cancellation is better than a no-show. Of course, make sure that you also follow the official procedures (if applicable).

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.

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 Set 1, due April 11
• Problem Set 2, due April 18
• Problem Set 3, due April 25
• Problem Set 4, due May 2
• Problem Set 5, due May 9
• Problem Set 6, due May 23
• Problem Set 7, due June 06
• Problem Set 8, due June 13
• Problem Set 9, due June 20
• Problem Set 10, due June 27
• Problem Set 11, due July 04
• Problem Set 12, due July 11

• Problem Set 1
• Problem Set 2
• Problem Set 3
• Problem Set 4
• Problem Set 5
• Problem Set 6
• Problem Set 7
• Problem Set 8
• Problem Set 9
• Problem Set 10
• Problem Set 11
• Problem Set 12

• Algorithmic Game Theory, edited by Nisan, Roughgarden, Tardos, and Vazirani, available online under “Resources”
• Twenty Lectures on Algorithmic Game Theory, by Tim Roughgarden; also see his original lecture notes that are available online
• Game Theory, Alive! by Karlin and Peres, available online
• Multiagent Systems by Shoham and Leyton-Brown, available online
• Lecture notes on Algorithmic Mechanism Design by Jason Hartline, available online