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052414 VU Concepts and Models of Knowledge Engineering (2019W)
Continuous assessment of course work
Labels
Summary
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Sa 07.09.2019 09:00 to Mo 23.09.2019 09:00
- Deregistration possible until Mo 14.10.2019 23:59
Registration information is available for each group.
Groups
Group 1
max. 25 participants
Language: English
LMS: Moodle
Lecturers
Classes (iCal) - next class is marked with N
Wednesday
02.10.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
(Kickoff Class)
Wednesday
20.11.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
21.11.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
27.11.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
28.11.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
04.12.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
05.12.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Monday
09.12.
16:45 - 18:15
Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
Wednesday
11.12.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
12.12.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
08.01.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
09.01.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
15.01.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
16.01.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
22.01.
13:15 - 14:45
Seminarraum 2, Währinger Straße 29 1.UG
Thursday
23.01.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
29.01.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
30.01.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Friday
31.01.
18:30 - 20:00
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Group 2
max. 25 participants
Language: English
LMS: Moodle
Lecturers
Classes (iCal) - next class is marked with N
Wednesday
02.10.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
(Kickoff Class)
Wednesday
20.11.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
21.11.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
27.11.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
28.11.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
04.12.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
05.12.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Monday
09.12.
16:45 - 18:15
Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
Wednesday
11.12.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
12.12.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
08.01.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
09.01.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
15.01.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
16.01.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
22.01.
13:15 - 14:45
Seminarraum 2, Währinger Straße 29 1.UG
Thursday
23.01.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
29.01.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
30.01.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Friday
31.01.
18:30 - 20:00
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Information
Aims, contents and method of the course
In this lecture, the goal is to gain expertise on the state of the art in knowledge engineering. Therefore, students explore the relevant theory and reinforce their knowledge in exercises.The lecture covers agent systems and approaches for knowledge representation, problem solving, reasoning and planning, handling uncertainty and learning.
Assessment and permitted materials
Two exams have to be written and weekly exercises on the lecture content have to be submitted. The exams will contain theory questions and applied problems, based on the lectures, a script with lecture content, and exercises. During the test, no unauthorized materials are allowed and all electronic devices have to be turned off.Missing class more than three times results in a negative grade.
Minimum requirements and assessment criteria
For a positive evaluation of the course, more or equal to 50% of requirements have to be fulfilled. The grading scale is defined as follows:
>= 50% - 4
>= 63% - 3
>= 75% - 2
>= 87% - 1
>= 50% - 4
>= 63% - 3
>= 75% - 2
>= 87% - 1
Examination topics
The exam topics comprise the content presented in the lectures, the topics of the exercises and the script.
Reading list
Script with lecture content
Moodle courseDimitris Karagiannis, Rainer Telesko: Wissensmanagement: Konzepte der künstlichen Intelligenz und des Softcomputing
Stuart J. Russell, Peter Norvig: Artificial Intelligence - A Modern Approach
Moodle courseDimitris Karagiannis, Rainer Telesko: Wissensmanagement: Konzepte der künstlichen Intelligenz und des Softcomputing
Stuart J. Russell, Peter Norvig: Artificial Intelligence - A Modern Approach
Association in the course directory
Module: WI2 KE
Last modified: Mo 07.09.2020 15:20