621.065 (18S) Uncertain Knowledge: Reasoning and Learning
Überblick
- Lehrende/r
- LV-Titel englisch Uncertain Knowledge: Reasoning and Learning
- LV-Art Vorlesung-Kurs (prüfungsimmanente LV )
- Semesterstunde/n 2.0
- ECTS-Anrechnungspunkte 4.0
- Anmeldungen 47 (25 max.)
- Organisationseinheit
- Unterrichtssprache Deutsch
- mögliche Sprache/n der Leistungserbringung Deutsch , Englisch
- LV-Beginn 23.03.2018
- eLearning zum Moodle-Kurs
Zeit und Ort
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 inkl. Einsatz von eLearning-Tools
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 BenotungsschemaPosition im Curriculum
- Diplom-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)
-
Knowledge Engineering (
2.0h PR / 4.0 ECTS)
-
Fach: Angewandte Informatik (LI 2.3)
(Pflichtfach)
-
2.Abschnitt
- 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)
-
4.2 Uncertain Knowledge: Reasoning and Learning (
2.0h VC / 4.0 ECTS)
-
Fach: Medieninformatik
(Wahlfach)
- 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)
-
5.3 Uncertain Knowledge: Reasoning and Learning (
2.0h VC / 4.0 ECTS)
-
Fach: Natural Language Processing
(Wahlfach)
- 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)
-
6.3 Uncertain Knowledge: Reasoning and Learning (
2.0h VC / 4.0 ECTS)
-
Fach: Softwareentwicklung
(Wahlfach)
- 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)
-
7.3 Uncertain Knowledge: Reasoning and Learning (
2.0h VC / 4.0 ECTS)
-
Fach: Wirtschaftsinformatik
(Wahlfach)
- 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)
-
Knowledge Engineering (
2.0h UE / 4.0 ECTS)
-
Fach: Medieninformatik
(Wahlfach)
- 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)
-
Knowledge Engineering (
2.0h UE / 4.0 ECTS)
-
Fach: Natural Language Processing
(Wahlfach)
- 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)
-
Knowledge Engineering (
2.0h UE / 4.0 ECTS)
-
Fach: Softwareentwicklung
(Wahlfach)
- 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)
-
Knowledge Engineering (
2.0h UE / 4.0 ECTS)
-
Fach: Wirtschaftsinformatik
(Wahlfach)
- 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)
-
Knowledge Engineering (
2.0h PR / 4.0 ECTS)
-
Fach: Knowledge Engineering
(Wahlfach)
- 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)
-
Knowledge Engineering (
2.0h UE / 4.0 ECTS)
-
Fach: Vertiefung Informatik
(Pflichtfach)
- 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)
-
Knowledge Engineering (
2.0h PR / 4.0 ECTS)
-
Fach: Knowledge Engineering
(Wahlfach)
- 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
-
4.1 Uncertain Knowledge: Reasoning and Learning (
0.0h VC / 4.0 ECTS)
-
Modul: Game Engineering
-
Fach: Gebundenes Wahlfach
(Wahlfach)
Gleichwertige Lehrveranstaltungen im Sinne der Prüfungsantrittszählung
-
Sommersemester 2019
- 621.065 VC Uncertain Knowledge: Reasoning and Learning (2.0h / 4.0ECTS)
-
Wintersemester 2018/19
- 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
-
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)