Course detail

Multi-valued Logic Applications

FSI-SALAcad. year: 2019/2020

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.

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.


Mathematical logic, fuzzy set theory


Not applicable.

Recommended optional programme components

Not applicable.

Recommended or required reading

Druckmüller, M.: Technické aplikace vícehodnotové logiky, PC- DIR , Brno 1998 (CS)
Jackson P.: Introduction to Expert Systems, Addison-Wesley 1999 (EN)

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.

Language of instruction


Work placements

Not applicable.


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.

Classification of course in study plans

  • Programme M2A-P Master's

    branch M-MAI , 2. year of study, winter semester, 4 credits, compulsory

Type of course unit



26 hours, compulsory

Teacher / Lecturer


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


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