192.099 Algorithmic Social Choice
Diese Lehrveranstaltung ist in allen zugeordneten Curricula Teil der STEOP.
Diese Lehrveranstaltung ist in mindestens einem zugeordneten Curriculum Teil der STEOP.

2020S, VU, 2.0h, 3.0EC
TUWEL

Merkmale

  • Semesterwochenstunden: 2.0
  • ECTS: 3.0
  • Typ: VU Vorlesung mit Übung

Lernergebnisse

Nach positiver Absolvierung der Lehrveranstaltung sind Studierende in der Lage...

After successful completion of the course, students will be able to:

  • explain and identify basic concepts, structures, and problems from collective decision making,
  • describe and design efficient algorithms, and analyze properties (e.g., computational complexity, existence or stability of solutions, characterizations) of problems arising in the context of collective decision making and related fields.

 

Inhalt der Lehrveranstaltung

The course addresses problems at the intersection of economics, social choice theory, and computer science. The focus is on processes of algorithmic decision making, such as voting rules or fair division. We discuss fundamental concepts from collective decision making and related topics and investigate algorithmic and computational aspects.

Specific topics include:

  • aggregating preferences (rank aggregation) and voting,
  • preference domain restrictions,
  • matchings under preferences,
  • algorithmic mechanism design,
  • cake cutting protocols,
  • fair allocation of recourses, and
  • judgment aggregation.

Methoden

The course will consist of lectures and exercises. The students will receive an exercise sheet 1-2 weeks before each exercise and are expected to submit their solutions in advance and also to be able to present the solutions on the whiteboard. Exercise sheets will be available for download.

Prüfungsmodus

Schriftlich und Mündlich

Weitere Informationen

ECTS Breakdown

  • Lectures + exercises: 25 h
  • Preparation and follow-up: 26 h
  • Exam preparation: 23 h
  • Exam: 1 h

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  • Sum:  75 h
  • ECTS: 3

 

Literature

  • U. Endriss, ed: Trends in Computational Social Choice. AI Access, 2017
  • F. Brandt, V. Conitzer, U. Endriss, J. Lang, and A. D. Procaccia, ed.: Handbook of Computational Social Choice. Cambridge University Press, 2015.
  • J. Rothe, ed.: Economics and Computation. An Introduction to Algorithmic Game Theory, Computational Social Choice, and Fair Division. Springer, 2015
  • Y. Shoham, K. Leyton-Brown: Multiagent Systems. Cambridge University Press, 2009.



Vortragende

Institut

LVA Termine

TagZeitDatumOrtBeschreibung
Mi.14:00 - 16:0004.03.2020 - 11.03.2020FAV Hörsaal 2 Algorithmische Social Choice
Algorithmic Social Choice - Einzeltermine
TagDatumZeitOrtBeschreibung
Mi.04.03.202014:00 - 16:00FAV Hörsaal 2 Algorithmische Social Choice
Mi.11.03.202014:00 - 16:00FAV Hörsaal 2 Algorithmische Social Choice

Leistungsnachweis

The final mark of each attendee depends on the final exam (60%) and his/her performance at the whiteboard exercises (40%).

LVA-Anmeldung

Von Bis Abmeldung bis
03.03.2020 00:00 10.04.2020 23:59 10.04.2020 23:59

Curricula

Literatur

Es wird kein Skriptum zur Lehrveranstaltung angeboten.

Vorkenntnisse

 Grundkenntnisse in Entwurf und Analyse von Algorithmen, z.B. aus

  1. Algorithmen und Datenstrukturen,
  2. Algorithmics (Master-VU),
  3. Komplexitätstheorie, etc.

 

Sprache

Englisch