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An introduction to algorithmic game theory, a relatively new field whose objective is to study formal models of
strategic environments and to design effective algorithms for them. This introductory course covers basic concepts
and methods that are illustrated with several practical applications. To successfully pass the course, it is
recommended to know basics from complexity theory.
Last update: Töpfer Pavel, doc. RNDr., CSc. (29.01.2018)
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The credit for the tutorial is given after obtaining at least one quater of all available points. The points are given for solving problems that are assigned during semester. The nature of the conditions does not allow repeated attempts for obtaining the credit. Obtaining the credit is necessary before the exam. Last update: Balko Martin, doc. RNDr., Ph.D. (07.10.2019)
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Noam Nisan, Tim Roughgarden, Eva Tardos, Vijay V. Vazirani: Algorithmic Game Theory, Cambridge University Press, 2007. Tim Roughgarden, Lecture Notes on Algorithmic Game Theory : http://theory.stanford.edu/~tim/f13/f13.html Last update: Töpfer Pavel, doc. RNDr., CSc. (29.01.2018)
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There will be oral exam with time for preparation of the answers. The material required for the exam will be the same as taught in the lecture. The exam may include easier or moderately difficult problems from these topics. The exam can be done online.
Last update: Balko Martin, doc. RNDr., Ph.D. (22.09.2020)
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Formal models in game theory Auctions, Myerson's Lemma Price of anarchy Nash equilibrium, Nash's Existence Theorem Finding equilibria, complexity class PPAD Correlated equilibiria and other variants Minimax Theorem Last update: Töpfer Pavel, doc. RNDr., CSc. (29.01.2018)
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