At London School of Economics
Fall 2018, 2017, 2016, 2014
Bachelor and Master-level course, also offered as distance learning course by University of London
Course guide: MA300.1, MA301, MA402
The course studies the theory of games and its applications in economics: Game trees with perfect information, NIM, combinatorial games. Backward induction. Extensive and strategic (normal) form of a game. Nash equilibrium. Commitment. Zero sum games, mixed strategies. Maxmin strategies. Nash equilibria in mixed strategies. Finding mixed-strategy equilibria for two-person games. Extensive games with information sets, behaviour strategies, perfect recall. If time permits: The Nash bargaining solution. Multistage bargaining.
Lecture notes and slides: Moodle (restricted)
Spring 2019, 2018, 2015
Algorithms and Programming
Course guide: MA314
This course provides the basic toolbox for the design and analysis of algorithms, with programming exercises in Python: Do you know how to multiply integers?; Sorting algorithms, Big-O notation; Working with Big-O Notation, Heap Sort; QuickSort, Beyond worst-case analysis, Randomized QuickSort; Lower bounds for comparison sorts, Sorting in linear time; Lists in Python, Stacks, Queues, Hashing; Breadth-first search, Depth-first search; Greedy algorithms: Prim’s algorithm, Dijkstra’s algorithm; Maximum Flow; PageRank and Blockchain
Slides: Moodle (restricted)
At ETH Zürich
Algorithmic Game Theory
Bachelor, Master, and PhD-level course
Taught together with Peter Widmayer
Course guide: 252-1407-00 L
Game theory provides a good model for the behavior and interaction of the selfish users and programs in large-scale distributed computer systems without central control. The course discusses algorithmic aspects of game theory, such as a general introduction to game theory, auctions, mechanisms, the costs of a central control optimum versus those of an equilibrium under selfish agents, and algorithms and complexity of computing equilibria.
Lecture Notes: ETH Coursepage
Algorithmic Game Theory Seminar
Master and PhD-level course
Taught together with Peter Widmayer and Sven Seuken
Course guide: 252-4302-00 S
In this seminar, we will discuss advanced topics in economics and computation (list of topics was made available in the kick-off meeting). Students review a paper, independently acquire the necessary background knowledge, and write a ca. 10 pages manuscript. They give a presentation (20 min) on the topic of their paper, and lead a short discussion (10 min) following their presentation. Students support each other as “buddies”.
Course homepage: UZH Coursepage