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Be English-friendly or any other language-friendly means that UC is taught in a language but can either of the
following conditions:
1. There are support materials in English / other language;
2. There are exercises, tests and exams in English / other language;
3. There is a possibility to present written or oral work in English / other language.
1
6.0
0.0 h/sem
36.0 h/sem
0.0 h/sem
0.0 h/sem
0.0 h/sem
0.0 h/sem
1.0 h/sem
37.0 h/sem
113.0 h/sem
0.0 h/sem
150.0 h/sem
Since year
2017/2018
Pre-requisites
Basic notions on calculus and linear algebra.
Objectives
The new economy created new tools that are in the intersection of computer science, mathematics and microeconomy. Game theory is the natural way to model them. The purpose of this course is for students to learn the main applications of game and incentives theories in computer science, to understand their need and main features. Some of the applications to be covered throughout the course are: -how to design auctions for live selling of advertising, google adwords. -how to match prospect students and universities, or how to match kidney donors and receivers in a kidney exchange market. -voting systems, how to rank webpages in web searches (rank aggregation).
-how to design peer to peer networks, which incentives should be given in order for the participants to upload as well as download and make the network efficiency be sustainable. -how, why and when to design reputation systems, uber, ebay, amazon, etc.
Program
1.Introduction. 2.Social choice (Voting). 3.Incentives in computer science. 4.Auction theory. 5. Mechanism design. 6.Kidney exchange and stable matching. 7.Selfish Routing and the price of anarchy.
Evaluation Method
The evaluation will be given by individual or group assignment (100%). If students fail to attain the goals of the assignment the grade will be given by a final exam (100%).
Teaching Method
The classes are run as theoretical-practical lectures. The theoretical exposition is followed by exercise solving and real life examples.
Observations
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Basic Bibliographic
Roughgarden, Tim. Twenty Lectures on Algorithmic Game Theory. Cambridge University Press, 2016.
Complementar Bibliographic
Nisan, Noam, et al., eds. Algorithmic game theory. Vol. 1. Cambridge: Cambridge University Press, 2007.
