Course detail
Technical Applications of Artificial Intelligence Methods
FSI-RUI Acad. year: 2021/2022 Summer semester
The course is intended for students of mathematical engineering and deals with the multi-valued logic theory, theory of linguistic varialble, linguistic models and theory of expert systems based on these topics. Also dealt with are the technical applications of multi-valued logic and expert systems in technical branches.
Language of instruction
Czech
Number of ECTS credits
5
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
Basic knowledge of mathematical logic, set theory and mathematical analysis
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 usage 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 N-MET-P: Mechatronics, Master's, compulsory
Programme N-IMB-P: Engineering Mechanics and Biomechanics, Master's
specialization BIO: Biomechanics, compulsory-optional
Programme N-IMB-P: Engineering Mechanics and Biomechanics, Master's
specialization IME: Engineering Mechanics, compulsory-optional
Type of course unit
Lecture
26 hours, optionally
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. Semantic interpretations of knowledge bases
6. Inference techniques and its implementation
7. Redundance a contradictions in knowledge bases
8. LMPS system
9. LMPS system – applications
10. Fuzzification and defuzzification problem
11. Technical applications of multi-valued logic and fuzzy sets theory
13. Expert systems
13. Overview of AI methods
Computer-assisted exercise
26 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