Games, networks and elections 1000-2D22GSW
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.
Main fields of studies for MISMaP
Type of course
Prerequisites (description)
Course coordinators
Term 2024: | Term 2023: |
Learning outcomes
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).
Assessment criteria
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).
Bibliography
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
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: