Algorithmic Game Theory (AGT)5 ECTS
(englische Bezeichnung: Algorithmic Game Theory)

Lehrveranstaltungen:

• • Algorithmic Game Theory (Optimization in Industry and Economy)
    (Vorlesung, 2 SWS, Yiannis Giannakopoulos, Mo, 14:00 - 16:00, H13; Sollten Sie sich für diesen Kurs interessieren, melden Sie sich im zugehörigen Studonkurs an. Link: https://www.studon.fau.de/crs4070964_join.html)
  • Übung Algorithmic Game Theory
    (Übung, 1 SWS, Yiannis Giannakopoulos)
  • Algorithmic Game Theory (Optimization in Industry and Economy)
    (Vorlesung, 2 SWS, Yiannis Giannakopoulos, Mo, 14:00 - 16:00, H13; Sollten Sie sich für diesen Kurs interessieren, melden Sie sich im zugehörigen Studonkurs an. Link: https://www.studon.fau.de/crs4070964_join.html)
  • Algorithmic Game Theory (Optimization in Industry and Economy)
    (Vorlesung, 2 SWS, Yiannis Giannakopoulos, Mo, 14:00 - 16:00, H13; Sollten Sie sich für diesen Kurs interessieren, melden Sie sich im zugehörigen Studonkurs an. Link: https://www.studon.fau.de/crs4070964_join.html)

Inhalt:

https://www.studon.fau.de/studon/goto.php?target=univis_2021w.Lecture.41307648

Lernziele und Kompetenzen:

Learning Objectives Upon successful completion of this module, students have a comprehensive understanding of the foundations of algorithmic game theory and algorithmic mechanism design. In particular, they can:
design and analyse efficient mechanisms for various settings involving rational selfish players, most notably Bayesian revenue-maximizing auctions quantify the loss in performance of a system due to selfish behaviour (price of anarchy), most notably in traffic routing understand the concept of differentiating between various equilibria outcomes and selecting the desired ones (potentials and equilibrium refinement) understand the concept of learning dynamics in game-playing, such as best-responses

Verwendbarkeit des Moduls / Einpassung in den Musterstudienplan:
Das Modul ist im Kontext der folgenden Studienfächer/Vertiefungsrichtungen verwendbar:

1. Computational and Applied Mathematics (Master of Science)
   (Po-Vers. 2017w | NatFak | Computational and Applied Mathematics (Master of Science) | Specialisation: Modeling and applied analysis (MApA) and optimization (Opti) | Algorithmic Game Theory)
2. Computational and Applied Mathematics (Master of Science)
   (Po-Vers. 2017w | NatFak | Computational and Applied Mathematics (Master of Science) | Specialisation: Numerical analysis and simulation (NASi) and optimization (Opti) | Algorithmic Game Theory)
3. Computational and Applied Mathematics (Master of Science)
   (Po-Vers. 2019w | NatFak | Computational and Applied Mathematics (Master of Science) | Gesamtkonto | Specialisation: Modeling and applied analysis (MApA) and optimization (Opti) | Algorithmic Game Theory)
4. Computational and Applied Mathematics (Master of Science)
   (Po-Vers. 2019w | NatFak | Computational and Applied Mathematics (Master of Science) | Gesamtkonto | Specialisation: Numerical analysis and simulation (NASi) and optimization (Opti) | Algorithmic Game Theory)
5. Data Science (Master of Science)
   (Po-Vers. 2021w | Gesamtkonto | Studienrichtung Databased optimization | Algorithmic Game Theory)
6. Wirtschaftsmathematik (Master of Science)
   (Po-Vers. 2019w | NatFak | Wirtschaftsmathematik (Master of Science) | Gesamtkonto | Mathematische Wahlpflichtmodule | Specialisation: Modeling and applied analysis (MApA) and optimization (Opti) | Algorithmic Game Theory)
7. Wirtschaftsmathematik (Master of Science)
   (Po-Vers. 2019w | NatFak | Wirtschaftsmathematik (Master of Science) | Gesamtkonto | Mathematische Wahlpflichtmodule | Specialisation: Numerical analysis and simulation (NASi) and optimization (Opti) | Algorithmic Game Theory)

Studien-/Prüfungsleistungen:

Algorithmic Game Theory (Prüfungsnummer: 50821)

Prüfungsleistung, mündliche Prüfung, Dauer (in Minuten): 15, benotet, 5 ECTS

Anteil an der Berechnung der Modulnote: 100.0 %

Erstablegung: WS 2021/2022, 1. Wdh.: WS 2021/2022

1. Prüfer:

Yiannis Giannakopoulos