(*) Leider ist diese Information in Deutsch nicht verfügbar.
Workload
Ausbildungslevel
Studienfachbereich
VerantwortlicheR
Semesterstunden
Anbietende Uni
3 ECTS
M1 - Master 1. Jahr
Artificial Intelligence
Martina Seidl
2 SSt
Johannes Kepler Universität Linz
Detailinformationen
Quellcurriculum
Masterstudium Artificial Intelligence 2025W
Lernergebnisse
Kompetenzen
(*)The students can analyze the strengths and limitations of various reasoning formalisms and from a pool of different formalisms, they can select a suitable formalism for efficiently encoding a specific reasoning task. They can employ reasoning tools to evaluate the encoding and they can interpret the results of the reasoning tools and map them back to the original reasoning task.
Fertigkeiten
Kenntnisse
(*)
understand multiple formalisms for symbolic reasoning (K2, K3)
employ symbolic reasoners for problem solving (K2, K3, K4)
formulate symbolic encodings (K4, K5, K6)
assess if a formalism is suitable for a specific application problem (K4)
(*)Students acquire knowledge of symbolic reasoning techniques and their underlying theory, focusing on their application in domains such as planning and formal verification. They learn how to encode application problems into formal systems and analyze the effectiveness of inference mechanisms, gaining insights into the advantages and limitations of symbolic reasoning in AI.
Beurteilungskriterien
(*)The evaluation is together with the exercise class and is based on:
Weekly online exercises
Projects in teams and presentations of the solutions
Short presentation of a recent topic related to the course
Alternatively, there is also an exam offered.
Lehrmethoden
(*)
Weekly lecture
Weekly exercises
Two encoding projects
Literature study/tool evaluation
Abhaltungssprache
Englisch
Literatur
(*)
Slides of the lecture
Recordings of the lectures
Links to recent literature
Solutions to some of the exercises
Lehrinhalte wechselnd?
Nein
Sonstige Informationen
(*)This lecture and the associated exercise course form an inseparable didactic unit. The learning outcomes presented here are achieved through the close interaction of the two courses.
Äquivalenzen
(*)201COMACALV18: VL Computer Algebra (3 ECTS)
Frühere Varianten
Decken ebenfalls die Anforderungen des Curriculums ab (von - bis) 993TARKPRAV20: VL Planning and Reasoning in Artificial Intelligence (2020W-2022S)
