Es ist eine neuere Version 2025W dieses Fachs/Moduls im Curriculum Master's programme Artificial Intelligence 2025W vorhanden.
Workload
Mode of examination
Education level
Study areas
Responsible person
Coordinating university
21 ECTS
Accumulative subject examination
M1 - Master's programme 1. year
Computer Science
Sepp Hochreiter
Johannes Kepler University Linz
Detailed information
Original study plan
Master's programme Artificial Intelligence 2022W
Objectives
Classical methods in AI rely on symbolic reasoning based on logic and mathematics. On the one hand, a focus of this elective track is on deductive reasoning, including model checking and theorem proving, techniques which are also essential for software and hardware verification. On the other hand, students can focus on specialized mathematical topics in the fields of analysis, numerics, and statistics, which underpin modern AI technologies.
Subject
The contents of this subject result from the contents of its courses.
Further information
Rules for the elective track "Symbolic AI and Mathematical Foundations": (a) Students need to complete 21 ECTS points in total from both sub-categories ("Symbolic AI" and "Mathematical Foundations"). (b) Students need to choose a “focus” sub-category from which at least 13.5 ECTS points have to be completed. If the focus is the sub-category “Symbolic AI”, the following courses must be completed:
993TASMKPLV22: VL Knowledge Representation and Learning (3 ECTS)
993TASMKPLU22: UE Knowledge Representation and Learning (1.5 ECTS)
993TASMPRAV22: VL Planning and Reasoning in Artificial Intelligence (3 ECTS)
993TASMPRAU22: UE Planning and Reasoning in Artificial Intelligence (1.5 ECTS).
