Games, networks and elections

computer science

Master's seminars

The following courses are thematically linked to the seminar and completing them will be useful (although not compulsory) to every student attending the seminar:

Coalitional game theory 1000-2M12TGK

Computational social choice theory 1000-2M09OTW

Auction theory 1000-2M13TAU

Implementation theory 1000-2M16TIM

Algorithmic aspects of game theory 1000-2M02AA

The seminar concerns research at the interface of computer science, artificial intelligence and economics. The topics of interest include game theory (both cooperative and non-cooperative), social networks analysis, social choice, as well as other topics related topics such as mechanism design, market design, and information economics.

Tematical scope of the seminar includes

1. Cooperative and non-cooperative game theory and their applications, in particular in computer science and artificial intelligence.

2. Social networks analysis, including axiomatic and algorithmic analysis of centrality measures.

3. Social choice theory and its applications, including issues related to fairness.

4. Auctions and other mechanisms for choosing outcomes for strategic agents.

5. Prediction markets, information economics, market design, contest design, and other topics at the interface of computer science, artificial intelligence and economics.

Algorithmic game theory, N. Nisan, T. Roughgarden, É. Tardos, V. Vazirani

Networks, Crowds, and Markets: Reasoning About a Highly Connected World, David Easley, Jon Kleinberg

Network Analysis: Methodological Foundations, Urlik Brandes, Thomas Erlebach

Handobook of computational social choice, Felix Brandt, Vincent Conitzer, Ulle Endriss, Jérôme Lang, Ariel D. Procaccia

Social and economic networks, Matthew O. Jackson

Connections: an introduction to the economics of networks, Sanjeev Goyal

Multiagent systems: algorithmic, game-theoretic, and Logical Foundations, Yoav Shoham, Kevin Leyton-Brown

Knowledge:

1. Has advanced knowledge in the area of multiagent systems and methods used in the field of intelligent systems.

Skills:

1. Has advanced skill of preparing oral presentation in polish as well as a foreign language, in the area of computer science or on the interface of computer science and other research areas (K_U11).

2. Is able to describe chosen problems and their solutions in the area of computer science in a way accessible to a non-expert; is able to prepare a multimedia presentation using IT tools (K_U12).

3. Is able to prepare a scientific case study in a selected subfield of computer science (in both polish and english language) (K_U13).

4. Has language skills in the area of computer science at the B2+ CEFRL level (K_U14).

5. Is able to self-educate and to determine the right directions for extending own knowledge (K_U15).

Competences:

1. Knows limitations of his/her knowledge, is willing to constantly upgrade and update his/her knowledge and raise qualifications within the field of computer science and related scientific areas and disciplines (K_K01)

2. Knows how to precisely formulate questions in order to deepen own understanding of the studied subject (in particular in contacts with non-computer scientists) or to find gaps in own reasoning about the subject (K_K02)

3. Is capable of working in teams, including interdisciplinary teams; understands the necessity of systematic work when working in long-term projects (K_K03).

4. Is able to formulate opinions about fundamental topics in computer sciences (K_K06).

5. Understands the need of systematicly updating own knowledge by reading scientific and poplar scientific journals (K_K08).

Giving a required number of presentations, submitting (and, possibly, correcting) their electronic versions and conspects

Activity during classes

Completing formal requirements (having an accepted topic of master thesis after the first year, submitting the thesis after the second year).