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| Detailed information |
| Original study plan |
Bachelor's programme Technical Mathematics 2025W |
| Learning Outcomes |
Competences |
| Students are able to apply the methods of mathematical
logic to deal with the vagueness inherent in natural language terms.
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| Skills |
Knowledge |
- 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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| Criteria for evaluation |
written exam
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| Methods |
Blackboard presentation
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| Language |
English and French |
| Study material |
P. Cintula, P. Hajek, C. Noguera (Eds.), Handbook of Mathematical Fuzzy Logic, College Publication, London 2011.
|
| Changing subject? |
No |
| Corresponding lecture |
(*)TM1WMVOFUZL: VL Fuzzy Logic (3 ECTS)
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| Earlier variants |
They also cover the requirements of the curriculum (from - to)
201WIMSMVLV23: VL Manyvalued Logic (2023W-2025S)
404LFMTMVLV20: VL Manyvalued Logic (2020W-2023S)
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