Universität Wien

052414 VU Concepts and Models of Knowledge Engineering (2019W)

3.00 ECTS (2.00 SWS), SPL 5 - Informatik und Wirtschaftsinformatik
Continuous assessment of course work

Summary

1 Karagiannis , Moodle
2 Karagiannis , Moodle

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 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

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 course

Dimitris 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