052413 VU Logical Foundations of Knowledge Engineering (2017W)
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 09.09.2017 09:00 to Su 24.09.2017 23:59
- Deregistration possible until Su 15.10.2017 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
04.10.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
05.10.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
11.10.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
12.10.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
18.10.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
19.10.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Monday
23.10.
18:30 - 20:00
Hörsaal 1, Währinger Straße 29 1.UG
Wednesday
25.10.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
09.11.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
15.11.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
16.11.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
22.11.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Friday
24.11.
17:30 - 20:00
Hörsaal 1, Währinger Straße 29 1.UG
Group 2
max. 25 participants
Language: English
LMS: Moodle
Lecturers
Classes (iCal) - next class is marked with N
Wednesday
04.10.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
05.10.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
11.10.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
12.10.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
18.10.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
19.10.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Monday
23.10.
18:30 - 20:00
Hörsaal 1, Währinger Straße 29 1.UG
Wednesday
25.10.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
09.11.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
15.11.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Thursday
16.11.
09:45 - 11:15
Hörsaal 3, Währinger Straße 29 3.OG
Wednesday
22.11.
13:15 - 14:45
Hörsaal 3, Währinger Straße 29 3.OG
Friday
24.11.
17:30 - 20:00
Hörsaal 1, Währinger Straße 29 1.UG
Information
Aims, contents and method of the course
In this lecture, the goal is to gain expertise in basics knowledge engineering. Therefore, students explore the relevant theory and reinforce their knowledge in exercises where approaches for knowledge representation and knowledge processing are employed. Topics like propositional logic, first-order logic and rule based systems are covered in this lecture and further applied in the Concepts and Models of Knowledge Engineering lecture.
Assessment and permitted materials
Twice during the semester a written test has to be passed. The test will contain theory questions and applied problems. During the test, no unauthorized materials are allowed and all electronic devices have to be turned off.
During the semester, homework assignments have to be submitted. Solutions have to be independent for each student.
In detail, the grade is constituted by:
* Written tests – 40 % + 40 %
* Homework assignments (Exercises) – 20%
Missing class more than three times results in a negative grade.
During the semester, homework assignments have to be submitted. Solutions have to be independent for each student.
In detail, the grade is constituted by:
* Written tests – 40 % + 40 %
* Homework assignments (Exercises) – 20%
Missing class more than three times results in a negative grade.
Minimum requirements and assessment criteria
The aim of the course is to learn and understand the logical foundations for knowledge engineering and how they can be applied.
To receive a positive grade, 50 out of 100 percent are required. Grades are as follows:
* sehr gut (1) >= 87,00%
* gut (2) >= 75,00%
* befriedigend (3) >= 62,00%
* genügend (4) >= 50,00 %
* nicht genügend (5) < 50,00 %
To receive a positive grade, 50 out of 100 percent are required. Grades are as follows:
* sehr gut (1) >= 87,00%
* gut (2) >= 75,00%
* befriedigend (3) >= 62,00%
* genügend (4) >= 50,00 %
* nicht genügend (5) < 50,00 %
Examination topics
Information, Knowledge & Knowledge Engineering
Knowledge Representation
Propositional & First-Order Logic: Introduction
Propositional Logic: Reasoning and Proof
First-Order Logic: Reasoning and Proof
Rule Based Systems
Fuzzy Logic
Knowledge Representation
Propositional & First-Order Logic: Introduction
Propositional Logic: Reasoning and Proof
First-Order Logic: Reasoning and Proof
Rule Based Systems
Fuzzy Logic
Reading list
Script with lecture content
Moodle courseDimitris Karagiannis, Rainer Telesko (2001), Wissensmanagement: Konzepte der künstlichen Intelligenz und des Softcomputing
Stuart J. Russell, Peter Norvig (2009), Artificial Intelligence - A Modern Approach
Moodle courseDimitris Karagiannis, Rainer Telesko (2001), Wissensmanagement: Konzepte der künstlichen Intelligenz und des Softcomputing
Stuart J. Russell, Peter Norvig (2009), Artificial Intelligence - A Modern Approach
Association in the course directory
Module: KE WI2
Last modified: Mo 07.09.2020 15:30