Inhalt

[ 993TASMKPLV22 ] VL Knowledge Representation and Learning

Versionsauswahl
Workload Education level Study areas Responsible person Hours per week Coordinating university
3 ECTS M1 - Master's programme 1. year (*)Artificial Intelligence Johannes Fürnkranz 2 hpw Johannes Kepler University Linz
Detailed information
Original study plan Master's programme Artificial Intelligence 2023W
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
Earlier variants They also cover the requirements of the curriculum (from - to)
993TARKKPLV21: VL Knowledge Representation and Learning (2021W-2022S)
993TARKSAIV19: VL Symbolic AI (2019W-2021S)
On-site course
Maximum number of participants -
Assignment procedure Direct assignment