155-0994/01 – Artificial Intelligence and Expert Systems (UIES)
Gurantor department | Department of Applied Informatics | Credits | 10 |
Subject guarantor | Ing. Petr Rozehnal, Ph.D. | Subject version guarantor | doc. Mgr. Miroslav Černý, Ph.D. |
Study level | postgraduate | Requirement | Compulsory |
Year | | Semester | winter + summer |
| | Study language | Czech |
Year of introduction | 2020/2021 | Year of cancellation | 2021/2022 |
Intended for the faculties | EKF | Intended for study types | Doctoral |
Subject aims expressed by acquired skills and competences
1. Know the basic principles of state space and methods of its searching based on the knowledge of artificial intelligence.
2. Understand the principles of knowledge representation within knowledge systems.
3. Understand the basic principles of creating individual components of expert systems and fuzzy expert systems.
4. Being able to apply the principles of fuzzy expert systems in their practical design and implementation.
Teaching methods
Individual consultations
Project work
Summary
The main goal of the course is to acquaint students with basic concepts and principles of artificial intelligence, state space and basic methods of its search, resolution method of predicate calculus, its application in proof of formulas and its applications in logic programming, selected concepts of knowledge representation, expert systems, fuzzy expert systems, fuzzy controllers and their economic applications.
Compulsory literature:
Recommended literature:
Way of continuous check of knowledge in the course of semester
- project development
- oral exam
E-learning
Other requirements
There are no further requirements for students attending this course.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
1. State space and its properties, basic methods of uninformed and informed state space search
2. Resolution method of first order predicate calculus and its use in proving the truth of formulas, Horn clause
3. The concept of knowledge and expert system and ways of representing knowledge within these systems, knowledge base, data base of expert systems and basic principles applied in inference mechanisms of expert systems
4. Fuzzy language variable and its language values, formulas of multivalued fuzzy language logic, truth values of formulas
5. Fuzzy expert systems and their basic properties, architecture of diagnostic, planning and hybrid fuzzy expert systems, methodology of creating knowledge base of fuzzy expert systems, queries and interpretation of fuzzy oriented rule expert systems, selected economic applications of fuzzy expert systems
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
Předmět neobsahuje žádné hodnocení.