[ 993TASMKPLV22 ] VL Knowledge Representation and Learning

Workload Education level Study areas Responsible person Hours per week Coordinating university
3 ECTS M1 - Master's programme 1. year (*)Artificial Intelligence Johannes F├╝rnkranz 2 hpw Johannes Kepler University Linz
Detailed information
Original study plan Master's programme Artificial Intelligence 2022W
Objectives Students are familiar with the basic concepts of logic-based programming and databases. They know how commonly used knowledge representation formalisms such as semantic nets and the semantic web are rooted in formal logic. They are able to understand and devise automated methods for learning in such formalisms.
Subject Foundations of Logic Programming and Logic-Based Databases, Explanation-Based Learning, Inductive Logic Programming, Relational Learning, Foundations of Knowledge Representation, Semantic Networks, Semantic Web, Case-Based Reasoning, Fuzzy Logic
Criteria for evaluation Exam at the end of the semester
Methods Lectures with Slides
Language English
Study material Lecture Slides, Pointers to relevant literature are given in the lecture
Changing subject? No
Further information Until term 2022S known as: 993TARKKPLV21 VL Knowledge Representation and Learning
until term 2021S known as: 993TARKSAIV19 VL Symbolic AI
On-site course
Maximum number of participants -
Assignment procedure Direct assignment