Computational social choice theory 1000-2M09OTW
The course will cover the following subjects:
1. Axiomatic analysis of single-winner rules. Paradoxes, impossibility theorems, and normative comparison of rules. Strategy-proofness and distortion (4 lectures).
2. Axiomatic and algorithmic analysis of multiwinner election rules. (3 lectures)
3. Impartial selection of items. (1 lecture)
4. Fair allocation of indivisible goods. (2 lectures)
5. Stable matchings. (1 lecture)
6. Kidney exchange. (1 lecture)
7. Prediction markets. (1 lecture)
8. Introduction to mechanism design. (1-2 lectures)
Type of course
Learning outcomes
Knowledge
1. Knowledge of fundamental problems and research directions in (computational) social choice theory.
2. Knowledge of most prominent voting rules and algorithms for making collective decisions.
3. Knowledge of methods of analysis of rules for collective decision making.
(K_W01, K_W02)
Skills:
* can use new techniques in own research work (K_U01)
* can use literature and research articles (in English) (K_U14)
Competences
* understands the need to systematically read scientific articles to broaden and expand knowledge (K_K08)
* can formulate precise questions to deepen own understanding of the topic or to find the missing pieces of the reasoning (K_K02)
Assessment criteria
There will be 14 homework assignments.
The course can be taken in a PhD programme as a "methodological" one. In that case, there is an additional requirement of solving at least one of the hardest (last in the list) problems on one of the homeworks.
Bibliography
Most of the content will be based on the following book:
Felix Brandt, Vincent Conitzer, Ulle Endriss, Jérôme Lang, Ariel D. Procaccia: Handbook of Computational Social Choice. Cambridge University Press 2016, ISBN 9781107446984
http://procaccia.info/papers/comsoc.pdf
Additionally, the lecture will cover material published recently in the field journals.
Additional information
Information on level of this course, year of study and semester when the course unit is delivered, types and amount of class hours - can be found in course structure diagrams of apropriate study programmes. This course is related to the following study programmes:
- Bachelor's degree, first cycle programme, Computer Science
- Master's degree, second cycle programme, Computer Science
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: