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Course detail

Multi-valued Logic Applications

Course unit code: FSI-SAL
Academic year: 2016/2017
Type of course unit: compulsory
Level of course unit: Master's (2nd cycle)
Year of study: 2
Semester: winter
Number of ECTS credits:
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.
Mode of delivery:
90 % face-to-face, 10 % distance learning
Mathematical logic, fuzzy set theory
Not applicable.
Recommended optional programme components:
Not applicable.
Course contents (annotation):
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.
Recommended or required reading:
Druckmüller, M.: Technické aplikace vícehodnotové logiky, PC- DIR , Brno 1998
Druckmüller, M.: Technické aplikace vícehodnotové logiky, PC- DIR , Brno 1998
Jackson P.: Introduction to Expert Systems, Addison-Wesley 1999
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.
Course curriculum:
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.

Type of course unit:

Lecture: 26 hours, optionally
Teacher / Lecturer: prof. RNDr. Miloslav Druckmüller, CSc.
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
seminars in computer labs: 13 hours, compulsory
Teacher / Lecturer: doc. PaedDr. Dalibor Martišek, Ph.D.
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

The study programmes with the given course