Inhalt

[ 993TASA22 ] Studienfach (*)Symbolic AI

Versionsauswahl
(*) Leider ist diese Information in Deutsch nicht verfügbar.
Workload Form der Prüfung Ausbildungslevel Studienfachbereich VerantwortlicheR Anbietende Uni
min. 13,5 ECTS Gliederung M1 - Master 1. Jahr Informatik Sepp Hochreiter Johannes Kepler Universität Linz
Detailinformationen
Quellcurriculum Masterstudium Artificial Intelligence 2022W
Ziele (*)The focus of this subject is on deductive reasoning, including model checking and theorem proving, techniques which are also essential for software and hardware verification.
Sonstige Informationen (*)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).
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