621.065 (18W) Uncertain Knowledge: Reasoning and Learning

Wintersemester 2018/19

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Erster Termin der LV
01.10.2018 09:00 - 12:00 , S.1.05
... keine weiteren Termine bekannt

Überblick

Lehrende/r
LV-Titel englisch
Uncertain Knowledge: Reasoning and Learning
LV-Art
Vorlesung-Kurs (prüfungsimmanente LV )
Semesterstunde/n
2.0
ECTS-Anrechungspunkte
4.0
Anmeldungen
24 (25 max.)
Organisationseinheit
Unterrichtssprache
Deutsch
mögliche Sprache/n der Leistungserbringung
Deutsch , Englisch
LV-Beginn
01.10.2018
eLearning
zum Moodle-Kurs

LV-Beschreibung

Intendierte Lernergebnisse

Students should recognize the issue of uncertainty inherent in many Artificial Intelligence applications, understand basic methods for dealing with this issue and learn to adopt and comprehend concrete algorithms that implement these methods. The focus in the first half of the semester will be on reasoning under uncertainty, whereas the second half will deal with learning.

Lehrmethodik

Lecture mixed with practical home and in-class exercises. Slides will be in English. Teaching language will be German unless there are non-German-speaking participants, otherwise English.


eLearning

Moodle

Inhalt/e

Provides an introduction to selected methods for dealing with uncertainty in Artificial Intelligence and Knowledge-Based Systems.

Topics

  • Uncertainty in AI Systems
  • Bayesian Inference
  • Theory and Construction of Bayesian Networks
  • Query Answering and Inference by means of Bayesian Networks
  • Unsupervised Machine Learning (Data Mining): Association Rule Mining
  • Supervised Machine Learning (Data Mining): Classification

Literatur

Adnan Darwiche. Modeling and Reasoning with Bayesian Networks. Cambridge University Press. 2009 P. 

Tan, M. Steinbach, V. Kumar. Introduction to Data Mining. Pearson. 2006 

Stuart Russell and Peter Norvig: Artificial Intelligence: A modern approach. Prentice Hall, 2009 

Judea Pearl: Probabilistic Reasoning in Intelligent Systems - Networks of Plausible Inference. Morgan Kaufmann Publishers, Inc. 1988 

D. Koller, N. Friedman. Probabilistic Graphical Models: Principles and Techniques. The MIT Press. 2009 

D. Barber. Bayesian Reasoning and Machine Learning. Cambridge University Press. 2012 

T. Mitchell. Machine Learning. McGraw Hill. 1997

Prüfungsinformationen

Prüfungsmethode/n

written examinations (60%) + homework exercises (40%) + collaboration points (bonus)

Prüfungsinhalt/e

theoretical and practical topics discussed in the course

Beurteilungskriterien/-maßstäbe

Will be published in Moodle at the beginning of the semester.

Beurteilungsschema

Note/Grade Benotungsschema

Position im Curriculum

  • Lehramtsstudium Unterrichtsfach Informatik und Informatikmanagement (SKZ: 884, Version: 04W.7)
    • 2.Abschnitt
      • Fach: Angewandte Informatik (LI 2.3) (Pflichtfach)
        • Knowledge Engineering ( 2.0h PR / 4.0 ECTS)
          • 621.065 Uncertain Knowledge: Reasoning and Learning (2.0h VC / 4.0 ECTS)
  • Bachelorstudium Angewandte Informatik (SKZ: 511, Version: 17W.1)
    • Fach: Medieninformatik (Wahlfach)
      • 4.2 Uncertain Knowledge: Reasoning and Learning ( 2.0h VC / 4.0 ECTS)
        • 621.065 Uncertain Knowledge: Reasoning and Learning (2.0h VC / 4.0 ECTS)
  • Bachelorstudium Angewandte Informatik (SKZ: 511, Version: 17W.1)
    • Fach: Natural Language Processing (Wahlfach)
      • 5.3 Uncertain Knowledge: Reasoning and Learning ( 2.0h VC / 4.0 ECTS)
        • 621.065 Uncertain Knowledge: Reasoning and Learning (2.0h VC / 4.0 ECTS)
  • Bachelorstudium Angewandte Informatik (SKZ: 511, Version: 17W.1)
    • Fach: Softwareentwicklung (Wahlfach)
      • 6.3 Uncertain Knowledge: Reasoning and Learning ( 2.0h VC / 4.0 ECTS)
        • 621.065 Uncertain Knowledge: Reasoning and Learning (2.0h VC / 4.0 ECTS)
  • Bachelorstudium Angewandte Informatik (SKZ: 511, Version: 17W.1)
    • Fach: Wirtschaftsinformatik (Wahlfach)
      • 7.3 Uncertain Knowledge: Reasoning and Learning ( 2.0h VC / 4.0 ECTS)
        • 621.065 Uncertain Knowledge: Reasoning and Learning (2.0h VC / 4.0 ECTS)
  • Bachelorstudium Angewandte Informatik (SKZ: 511, Version: 12W.1)
    • Fach: Medieninformatik (Wahlfach)
      • Knowledge Engineering ( 2.0h UE / 4.0 ECTS)
        • 621.065 Uncertain Knowledge: Reasoning and Learning (2.0h VC / 4.0 ECTS)
  • Bachelorstudium Angewandte Informatik (SKZ: 511, Version: 12W.1)
    • Fach: Natural Language Processing (Wahlfach)
      • Knowledge Engineering ( 2.0h UE / 4.0 ECTS)
        • 621.065 Uncertain Knowledge: Reasoning and Learning (2.0h VC / 4.0 ECTS)
  • Bachelorstudium Angewandte Informatik (SKZ: 511, Version: 12W.1)
    • Fach: Softwareentwicklung (Wahlfach)
      • Knowledge Engineering ( 2.0h UE / 4.0 ECTS)
        • 621.065 Uncertain Knowledge: Reasoning and Learning (2.0h VC / 4.0 ECTS)
  • Bachelorstudium Angewandte Informatik (SKZ: 511, Version: 12W.1)
    • Fach: Wirtschaftsinformatik (Wahlfach)
      • Knowledge Engineering ( 2.0h UE / 4.0 ECTS)
        • 621.065 Uncertain Knowledge: Reasoning and Learning (2.0h VC / 4.0 ECTS)
  • Bachelorstudium Informatik (SKZ: 521, Version: 09W.3)
    • Fach: Knowledge Engineering (Wahlfach)
      • Knowledge Engineering ( 2.0h PR / 4.0 ECTS)
        • 621.065 Uncertain Knowledge: Reasoning and Learning (2.0h VC / 4.0 ECTS)
  • Masterstudium Angewandte Informatik (SKZ: 911, Version: 13W.1)
    • Fach: Vertiefung Informatik (Pflichtfach)
      • Knowledge Engineering ( 2.0h UE / 4.0 ECTS)
        • 621.065 Uncertain Knowledge: Reasoning and Learning (2.0h VC / 4.0 ECTS)
  • Masterstudium Informatik (SKZ: 921, Version: 09W.1)
    • Fach: Knowledge Engineering (Wahlfach)
      • Knowledge Engineering ( 2.0h PR / 4.0 ECTS)
        • 621.065 Uncertain Knowledge: Reasoning and Learning (2.0h VC / 4.0 ECTS)
  • Masterstudium Mathematics (SKZ: 401, Version: 18W.1)
    • Fach: Informatics (Wahlfach)
      • 8.4 Uncertain Knowledge: Reasoning and Learning ( 2.0h VC / 4.0 ECTS)
        • 621.065 Uncertain Knowledge: Reasoning and Learning (2.0h VC / 4.0 ECTS)
  • Masterstudium Technische Mathematik (SKZ: 401, Version: 13W.1)
    • Fach: Informatik (Wahlfach)
      • Knowledge Engineering ( 2.0h UE / 4.0 ECTS)
        • 621.065 Uncertain Knowledge: Reasoning and Learning (2.0h VC / 4.0 ECTS)
  • Erweiterungscurriculum Vertiefung der Informatik (Version: 16W.1)
    • Fach: Wissensverarbeitung (Wahlfach)
      • Knowledge Engineering ( 0.0h UE / 4.0 ECTS)
        • 621.065 Uncertain Knowledge: Reasoning and Learning (2.0h VC / 4.0 ECTS)
  • Masterstudium Game Studies and Engineering (SKZ: 992, Version: 17W.2)
    • Fach: Gebundenes Wahlfach (Wahlfach)
      • Modul: Game Engineering
        • 4.1 Uncertain Knowledge: Reasoning and Learning ( 0.0h VC / 4.0 ECTS)
          • 621.065 Uncertain Knowledge: Reasoning and Learning (2.0h VC / 4.0 ECTS)
            Absolvierung im 1., 2., 3. Semester empfohlen

Gleichwertige Lehrveranstaltungen im Sinne der Prüfungsantrittszählung

Sommersemester 2019
  • 621.065 VC Uncertain Knowledge: Reasoning and Learning (2.0h / 4.0ECTS)
Sommersemester 2018
  • 621.065 VC Uncertain Knowledge: Reasoning and Learning (2.0h / 4.0ECTS)
Wintersemester 2017/18
  • 621.065 VC Uncertain Knowledge: Reasoning and Learning (2.0h / 4.0ECTS)
Sommersemester 2017
  • 621.065 VC Uncertain Knowledge: Reasoning and Learning (2.0h / 4.0ECTS)
Wintersemester 2016/17
  • 621.065 VC Uncertain Knowledge: Reasoning and Learning (2.0h / 4.0ECTS)
Sommersemester 2016
  • 621.065 VC Uncertain Knowledge: Reasoning and Learning (2.0h / 4.0ECTS)
Wintersemester 2015/16
  • 621.065 VC Uncertain Knowledge: Reasoning and Learning (2.0h / 4.0ECTS)
  • 621.066 VC Uncertain Knowledge: Reasoning and Learning (2.0h / 4.0ECTS)
Sommersemester 2015
  • 621.065 VK Uncertain Knowledge: Reasoning and Learning (2.0h / 4.0ECTS)
Wintersemester 2014/15
  • 621.065 VK Uncertain Knowledge: Reasoning and Learning (2.0h / 4.0ECTS)