| Detailinformationen |
| Quellcurriculum |
Masterstudium Artificial Intelligence 2023W |
| Ziele |
(*)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.
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| Lehrinhalte |
(*)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
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| Beurteilungskriterien |
(*)Exam at the end of the semester
|
| Lehrmethoden |
(*)Lectures with Slides
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| Abhaltungssprache |
Englisch |
| Literatur |
(*)Lecture Slides, Pointers to relevant literature are given in the lecture
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| Lehrinhalte wechselnd? |
Nein |
| Frühere Varianten |
Decken ebenfalls die Anforderungen des Curriculums ab (von - bis)
993TARKKPLV21: VL Knowledge Representation and Learning (2021W-2022S)
993TARKSAIV19: VL Symbolic AI (2019W-2021S)
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