Course detail
Multi-valued Logic Applications
FSI-SAL Acad. year: 2019/2020 Winter semester
The course is intended especially for students of mathematical engineering. It includes the theory of multi-valued logic, theory of linguistic variable and linguistic models and theory of expert systems based on these topics. Particular technical applications of these mathematical teories are included as a practice.
Language of instruction
Czech
Number of ECTS credits
4
Supervisor
Department
Learning outcomes of the course unit
Knowledge of multi-valued logic, fuzzy sets theory and its use in technical applications, including practical experience with today´s expert systems.
Prerequisites
Mathematical logic, fuzzy set theory
Planned learning activities and teaching methods
The course is taught through lectures explaining the basic principles and theory of the discipline. Exercises are focused on practical topics presented in lectures.
Assesment methods and criteria linked to learning outcomes
Course-unit credit is awarded on condition of having worked out a semester work.
The exam has a written and oral part.
Aims
The aim of the course is to provide students with information about the use of Multi-valued logic in technical applications.
Specification of controlled education, way of implementation and compensation for absences
Atendance at seminars is controlled. An absence can be compensated for via solving additional problems.
The study programmes with the given course
Programme M2A-P: Applied Sciences in Engineering, Master's
branch M-MAI: Mathematical Engineering, compulsory
Type of course unit
Lecture
26 hours, compulsory
Teacher / Lecturer
Syllabus
1. Multi-valued logic, formulae
2. T-norms, T-conorms, generalized implications
3. Linguistic variables and linguistic models
4. Knowledge bases of expert systems
5-6. Semantic interpretations of knowledge bases
7. Inference techniques and its implementation
8. Redundance a contradictions in knowledge bases
9. LMPS system
10. Fuzzification and defuzzification problem
11. Technical applications of multi-valued logic and fuzzy sets theory
12. Expert systems
13. Overview of AI methods
Computer-assisted exercise
13 hours, compulsory
Teacher / Lecturer
Syllabus
1. Multi-valued logic, formulae
2. Lukasziewicz logic
3-4. Linguistic variables and linguistic models
5. Semester work specification
6. LMPS system – linguistic variables
7. LMPS system – statements
8. LMPS system – question and reply interpretation
9. LMPS system – debugger and redundance detection
10. LMPS system – contradictions detection and removing
11-12. Semester work consultation
13. Delivery of semester work