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#40910 / #2

SS 2019 - SS 2019

English

AI & Social Choice

6

Walsh, Toby

Benotet

Portfolioprüfung

English

Zugehörigkeit


Fakultät IV

Institut für Softwaretechnik und Theoretische Informatik

34359201 FG Algorithmic Decision Theory (ADT)

Keine Angabe

Kontakt


Keine Angabe

Aleksandrov, Martin Damyanov

martin.aleksandrov@tu-berlin.de

http://www.isti.tu-berlin.de/adt/menue/algorithmic_decision_theory/

Lernergebnisse

The aim of this course is to train students on basic research skills that are often not in the prime focus of a regular university course. On successful completion of the module, students will be able to: • develop mathematical models, • describe and design (efficient) algorithms • write a scientific report/paper • review a scientific report/paper • analyze properties of algorithms • develop critical thinking • improve their academic writing

Lehrinhalte

The module ,,AI & Social Choice” addresses social problems at the interface of artificial intelligence, fair division, economy and computer science. It is well-known that there is a large gap between academia and industry even in regard to AI. The main aim of this course is to partially cover this gap by giving to students the opportunity to work on state-of-the-art research projects. The projects integrate concepts from economics, game-theory, social choice and machine learning. • game theory and fair division • economic concepts in fair division • games with fair exchanges • deterministic algorithms for fair division • randomized algorithms for fair division • online algorithms for fair division • manipulation and control in fair division • machine learning and fair division Each registered student will receive the below benefits: • an interesting research project • an individual supervision on their project • a constructive feedback on their progress • an opportunity to co-author a scientific paper • an exposure to state-of-the-art research

Modulbestandteile

Compulsory area

Die folgenden Veranstaltungen sind für das Modul obligatorisch:

LehrveranstaltungenArtNummerTurnusSpracheSWS ISIS VVZ
Fair Division PraktikumPR9201 L 001WiSe/SoSeen4
ISIS-Kurssuche nach Veranstaltungen des Moduls

Arbeitsaufwand und Leistungspunkte

Fair Division Praktikum (PR):

AufwandbeschreibungMultiplikatorStundenGesamt
Homework15.04.0h60.0h
Attendance15.04.0h60.0h
Pre/post preparation15.04.0h60.0h
180.0h(~6 LP)
Der Aufwand des Moduls summiert sich zu 180.0 Stunden. Damit umfasst das Modul 6 Leistungspunkte.

Beschreibung der Lehr- und Lernformen

The project materials are distributed to students in the form of references. The projects are accompanied by supervised meetings on an individual basis with each student when project-specific details are discussed.

Voraussetzungen für die Teilnahme / Prüfung

Wünschenswerte Voraussetzungen für die Teilnahme an den Lehrveranstaltungen:

Obligatory knowledge: Algorithms, Mathematics. Preferable knowledge: Economics, Computational Complexity, Programming Preferable skills: Latex and either C, C++, Java, Perl or Python Mandatory requirements: None

Verpflichtende Voraussetzungen für die Modulprüfungsanmeldung:

Dieses Modul hat keine Prüfungsvoraussetzungen.

Abschluss des Moduls

Benotung

Benotet

Prüfungsform

Portfolio examination

Art der Portfolioprüfung

100 Punkte insgesamt

Sprache(n)

English

Prüfungselemente

NamePunkteKategorieDauer/Umfang
Supervision15mündlich>80% attendance
Report70schriftlich>10 pages
Review10schriftlich60min/>2 pages
Discussion5mündlich30min

Notenschlüssel

Notenschlüssel »Notenschlüssel 2: Fak IV (2)«

Gesamtpunktzahl1.01.31.72.02.32.73.03.33.74.0
100.0pt95.0pt90.0pt85.0pt80.0pt75.0pt70.0pt65.0pt60.0pt55.0pt50.0pt

Prüfungsbeschreibung (Abschluss des Moduls)

The exam consists of four components: a supervision, a report, a review and a discussion. Each component is mandatory for a successful completion of the course. Supervision: Each student is advised to attend at least 80% (i.e. 12 weeks) of the classes and actively participate in a discussion with their supervisors. They are expected to read papers during classes and ask questions relevant to their projects. Report: Each student is expected to write a report of at least 10 pages during the semester. The reports should contain the scientific (theoretical and empirical) findings of students on their projects: introduction (~2 pages), literature review (~2 pages) and results (~6 pages). The reports should be submitted prior to the date for the review. Review: The review aims to train students to important research skills: critical mindfulness, constructive feedback, justified argumentation. This part of the portfolio is written and at the end of the semester in a classroom. The duration of it is 60 min. Each student receives a report of a fellow student. The students might receive a scientific paper in case not enough reports are submitted. Each student is expected to write a report of at least 2 pages during the time limit with their objective evaluation of the results in the report of their fellow. Discussion: The discussion aims to train students to clearly formulate and state their findings. This part of the portfolio is oral and it examines the understanding of each student about the results in their own report and the feedback in their review. The duration of it is 30 min per student. Each student will be examined separately. All students will be examined after the date of the review.

Dauer des Moduls

Für Belegung und Abschluss des Moduls ist folgende Semesteranzahl veranschlagt:
1 Semester.

Dieses Modul kann in folgenden Semestern begonnen werden:
Winter- und Sommersemester.

Maximale teilnehmende Personen

Die maximale Teilnehmerzahl beträgt 10.

Anmeldeformalitäten

Please register at QISPOS OR directly at the examination office within 6 weeks after the beginning of the course.

Literaturhinweise, Skripte

Skript in Papierform

Verfügbarkeit:  nicht verfügbar

 

Skript in elektronischer Form

Verfügbarkeit:  verfügbar
Zusätzliche Informationen:

 

Literatur

Empfohlene Literatur
F. Brandt, V. Conitzer, U. Endriss, J. Lang, and A. Procaccia, editors. Handbook of Computational Social Choice. Cambridge University Press, 2016.
J. Rothe, ed.: Economics and Computation. An Introduction to Algorithmic Game Theory, Computational Social Choice, and Fair Division. Springer, 2015.
N. Nisan, T. Roughgarden, E. Tardos, and V. Vazirani. Algorithmic Game Theory. Cambridge University Press, 2007.
Y. Shoham and K. Leyton-Brown. Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations. Cambridge University Press, 2009.
U. Endriss, editor. Trends in Computational Social Choice. AI Access, 2017.

Zugeordnete Studiengänge


Diese Modulversion wird in folgenden Studiengängen verwendet:

Studiengang / StuPOStuPOsVerwendungenErste VerwendungLetzte Verwendung
Dieses Modul findet in keinem Studiengang Verwendung.

Sonstiges

Keine Angabe