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Lecturer(s)
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Mrkvička Miroslav, doc. Ing. Ph.D.
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Course content
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1. Introduction - basic concepts, motivation, (a little) history 2 - 3. Problem solving: uninformed and informed methods 4. Games, task decomposition, AND/OR graphs, evolutionary and genetic algorithms 5. Classification, recognition, clustering and regression - basic concepts 6. Feature-based recognition methods 7. Structural recognition methods 8. Neural networks 9. Introduction to knowledge representation 10. Nervous system, brain, senses, memory, language and speech 11. Intelligent agents 12. Natural language processing 13. Summary, discussion
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Learning activities and teaching methods
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Interactive lecture, E-learning, Laboratory work, Skills demonstration, Students' self-study, Self-study of literature
- Preparation for laboratory testing; outcome analysis (1-8)
- 20 hours per semester
- Contact hours
- 39 hours per semester
- Preparation for an examination (30-60)
- 40 hours per semester
- Team project (50/number of students)
- 16 hours per semester
- Practical training (number of hours)
- 26 hours per semester
- Presentation preparation (report) (1-10)
- 5 hours per semester
- Preparation for formative assessments (2-20)
- 10 hours per semester
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| prerequisite |
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| Knowledge |
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| to apply knowledge of mathematical analysis, linear algebra, probability theory, and mathematical statistics |
| to study specialized literature and recommended computer resources (manuals, Web pages etc.) |
| to create special program modules in higher programming languages (Java, C, C#, Prolog,...) |
| Skills |
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| používat získané znalosti z matematiky |
| samostatně studovat problematiku z dodaných studijních materiálů |
| aktivně používat znalosti z použití vyšších programovacích jazyků |
| vytvářet efektivní programové struktury ve vyšších programovacích jazycích |
| Competences |
|---|
| N/A |
| N/A |
| N/A |
| N/A |
| N/A |
| N/A |
| N/A |
| má znalosti z oblasti vytváření efektivních programových struktur a jejich snadného ladění |
| learning outcomes |
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| Knowledge |
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| basic knowledge about the artificial intelligence methods, methods of problem solving and recognition or classification methods |
| to create efective techniques and programming tools solving the problems by specialized methods of artificial intelligence |
| to create good program documentation of the realized program system |
| Skills |
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| efective use of techniques and programming tools for software development with the aim to create a specialized software for simulation and solving above mentioned methods |
| to propose simple logic systems and to verificate their features, to study the theory of logic systems and the implementation of such systems in specialized programming languages |
| to propose and develope knowledge based systems and procedures for knowledge derivation using the standard database systems |
| to apply modern systems for problem solving tasks (evolutionary and genetic algorithms, intelligent agents, modern software development techniques), to realize of such systems and verificate their properties |
| Competences |
|---|
| N/A |
| N/A |
| N/A |
| N/A |
| student dokáže vytvářet efektivní programové struktury podle zásad koncepce programových produktů pro oblast umělé inteligence |
| teaching methods |
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| Knowledge |
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| Interactive lecture |
| Laboratory work |
| E-learning |
| Self-study of literature |
| Skills |
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| Laboratory work |
| Skills demonstration |
| Individual study |
| Competences |
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| E-learning |
| Task-based study method |
| Self-study of literature |
| Students' portfolio |
| assessment methods |
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| Knowledge |
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| Combined exam |
| Test |
| Individual presentation at a seminar |
| Seminar work |
| Skills |
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| Skills demonstration during practicum |
| Individual presentation at a seminar |
| Competences |
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| Seminar work |
| Individual presentation at a seminar |
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Recommended literature
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Kubík, A. Inteligentní agenty - tvorba aplikačního software na bázi multiagentových systémů. Brno, 2007.
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Lukasová, Alena. Formální logika v umělé inteligenci. Vyd. 1. Brno : Computer Press, 2003. ISBN 80-251-0023-5.
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Mařík, Vladimír a kol. Umělá inteligence (2). Academia, Praha, 1997.
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Mařík, Vladimír a kol. Umělá inteligence (3). Academia, Praha, 2001.
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Mařík, Vladimír a kol. Umělá inteligence (4). Academia, Praha, 2003.
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Mařík, Vladimír. Umělá inteligence (1). Academia, Praha, 1993. ISBN 80-200-0496-3.
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Nilsson, Nils J. Principles of Artificial Intelligence. Springer Verlag, Berlin, 1982.
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Peter Norvig, Stuart Russell. Artificial Intelligence: A Modern Approach, Global Edition. 2021. ISBN 1292401133.
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V. Mařík, O. Štěpánková, J. Lažanský a kol. Umělá inteligence (5). 2007.
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