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Detailinformationen |
Quellcurriculum |
Bachelorstudium Technische Mathematik 2025W |
Lernergebnisse |
Kompetenzen |
(*)Students are able to apply the methods of mathematical
logic to deal with the vagueness inherent in natural language terms.
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Fertigkeiten |
Kenntnisse |
(*)- understand the notion of vagueness and the approach to deal with vagueness by means of logic
- be able to design a formal framework for modelling situations/processes involving vagueness
- design and apply a suitable proof system for model-theoretically defined propositional logics,
- determine the algebraic semantics of a (possibly non-classical) propositional logic
- prove the (algebraic, standard) completeness of a (possibly non-classical) propositional logic
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(*)Basics of lattice theory, model-theoretic definition of propositional
logics, Hilbert-style proof systems, soundness and completeness,
classical propositional logic, Boolean algebras, t-norm based
many-valued logics, residuated lattices, Basic Logic, BL-algebras,
Lukasiewicz logic, MV-algebras.
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Beurteilungskriterien |
(*)written exam
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Lehrmethoden |
(*)Blackboard presentation
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Abhaltungssprache |
English |
Literatur |
(*)P. Cintula, P. Hajek, C. Noguera (Eds.), Handbook of Mathematical Fuzzy Logic, College Publication, London 2011.
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Lehrinhalte wechselnd? |
Nein |
Äquivalenzen |
TM1WMVOFUZL: VL Fuzzy Logic (3 ECTS)
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Frühere Varianten |
Decken ebenfalls die Anforderungen des Curriculums ab (von - bis) 201WIMSMVLV23: VL Manyvalued Logic (2023W-2025S) 404LFMTMVLV20: VL Manyvalued Logic (2020W-2023S)
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