Algorithmic Game Theory

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Algorithmic Game Theory, Lecture 2 (Mechanism Design Basics)

Some of the information below is still from the prior year, It will be updated during the course. The lecture times for the course are Mondays and Thursdays, , both in room G. There is also a weekly tutorial for this course, starting in Week 3.

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There will be several tutorial groups one on Wendesday, one on Thursday to choose from. Lectures Lecture 1: What is Game Theory? No required reading. Reference texts for the entire course see slides of lecture 1 for a more comprehensive list : K. Leyton-Brown and Y.


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Shoham, "Essentials of Game Theory", A short book, available electronically from the Edinburgh University Library. Nisan, T. Roughgarden, E.


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    Typical questions concern the incentives in such environments - will the agents agree on a common routing pattern? Is there more than one such stable outcome? Is it "fair" or "efficient"?


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    3. Algorithmic game theory!

    Will the dynamics evolving from selfish behavior converge and how long does this take? Instead, you should be able to explain the idea, where we started from, where ended up, which steps we took on the way. You can take the exam in English, German, or any mix of these languages.

    Academic Aims

    As with any oral exam, it is an ideal preparation to practice responding to questions with fellow student. Especially, if you prefer to prepare the exam on your own, you should try explaining concepts. It really helps to askew typical questions aloud — even if no one listens. 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.

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    Algorithmic Game Theory SS

    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. 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. You should bring a solid background in algorithms and calculus.

    6.853: Algorithmic Game Theory and Data Science

    No prior knowledge on game theory is required. Specialized knowledge about certain algorithms is not necessary. Sidebar Home. Teaching SoSe Algorithmic Game Theory and the Internet. Seminar Advanced Algorithms Blum. Seminar Advanced Algorithms Kesselheim.

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