Course detail

Technical Applications of Artificial Intelligence Methods

FSI-RUIAcad. year: 2015/2016

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

Mode of study

Not applicable.

Guarantor

prof. RNDr. Miloslav Druckmüller, CSc.

Department

Institute of Mathematics (ÚM)

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

Co-requisites

Not applicable.

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.

Course curriculum

Not applicable.

Work placements

Not applicable.

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.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Not applicable.

Recommended reading

Not applicable.

Classification of course in study plans

  • Programme N3901-2 Master's

    branch M-MET , 1 year of study, summer semester, compulsory-optional

Type of course unit

 

Lecture

26 hod., 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. 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 hod., compulsory

Teacher / Lecturer

prof. RNDr. Miloslav Druckmüller, CSc.

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