| Course Unit Code | Course Unit Title | Number of ECTS Credits Allocated |
|---|
| 545-0029/02 | Applied Artificial Intelligence | 5 ECTS credits |
| Type of Course Unit | Compulsory |
|---|
| Level of Course Unit | Second Cycle |
|---|
| Year of Study | Second Year |
|---|
| Semester when the Course Unit is delivered | Winter Semester |
|---|
| Mode of Delivery | Face-to-face |
|---|
| Language of Instruction | Czech |
|---|
| Prerequisites and Co-Requisites | Course succeeds to compulsory courses of previous semester |
|---|
| Name of Lecturer(s) | Personal ID | Name |
|---|
| KEB30 | doc. Dr. Ing. Vladimír Kebo |
| REP75 | Ing. Michal Řepka, Ph.D. |
| Learning Outcomes of the Course Unit |
|---|
The goal is to build an advanced knowledge of control theory and system theory and basic knowledge of artificial intelligence. This knowledge is further developed for application areas of problems, job scheduling, theorem proving, inductive learning, neural networks and the application of evolutionary methods and algorithms and artificial life.
|
| Recommended Optional Programme Components |
|---|
| Common optional components are not offered, students of special interest can participate in departmental activities or can arrange consulting hours with lecturer. |
| Course Contents |
|---|
The roots of AI, the basic directions
Methods of representation and knowledge processing, knowledge systems
Qualitative modeling, planning systems
Expert systems, semantic nets, frames, and the inference rule's Network
Search knowledge and data from databases
Fuzzy systems and their applications
Artificial neural networks, neuron models, back propagation algorithm, the structure of ANN
Application of artificial neural networks
Machine learning and learning systems, learning with a teacher and no teacher
Recognition and computer vision, signs, structures, computer vision, visualization
Artificial Life, SWARM system, bio-cybernetics
Virtual reality, the languages ??of VR, VR applications
Evolutionary algorithms and systems, genetic algorithms
Application of artificial intelligence in industry and the cybernetic systems. |
| Recommended or Required Reading |
|---|
| Required Reading: |
|---|
| RUSSEL, S., NORVIG, P.: Artificial Intelligence, a Modern Approach, Pearson Education Inc., 2003, ISBN 0-13-080302-2, 932 pp |
1) Jiroušek,R. : Metody reprezentace a zpracování znalostí v umělé
inteligenci. VŠE Praha, 1995
2) Kotek,Z. a kol. : Adaptivní a učící se systémy. SNTL Praha, 1980
3) Mařík,V. a kol. : Umělá inteligence I. Academia Praha, 1993
4) Pokorný,M.: Řídící systémy se znalostní bází. Skripta VŠB-TU Ostrava, 1995
5) Vondrák,I..: Umělá inteligence a neuronové sítě. Skripta VŠB-TU Ostrava,
1994
6) http://alife.tuke.sk/
|
| Recommended Reading: |
|---|
| Literature recommended by the supervisor to the specific topic BP / DP |
| Literatura doporučená vedoucím práce k danému konkrétnímu tématu BP/DP. |
| Planned learning activities and teaching methods |
|---|
| Lectures, Seminars, Tutorials, Project work |
| Assesment methods and criteria |
|---|
| Task Title | Task Type | Maximum Number of Points
(Act. for Subtasks) | Minimum Number of Points for Task Passing |
|---|
| Exercises evaluation and Examination | Exercises evaluation and Examination | 100
(100) | 51 |
| Exercises evaluation | Exercises evaluation | 33
(33) | 0 |
| Project | Project | 33
| 0 |
| Examination | Examination | 67
(67) | 0 |
| Written examination | Written examination | 33
| 0 |
| Oral | Oral | 34
| 0 |
| Work placement(s) |
|---|
| Course does not contain work placement. |
