FPF:UIN1009 Artificial Intelligence - Course Information
UIN1009 Artificial Intelligence
Faculty of Philosophy and Science in OpavaSummer 2023
- Extent and Intensity
- 2/0/0. 4 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- doc. Ing. Petr Sosík, Dr. (lecturer)
- Guaranteed by
- doc. Ing. Petr Sosík, Dr.
Institute of Computer Science – Faculty of Philosophy and Science in Opava - Timetable
- Tue 9:45–11:20 B2
- Prerequisites (in Czech)
- ! UIAI042 Artificial Intelligence
Tento předmět je vhodný pouze pro studenty, kteří již absolvovali předmět Úvod do logiky. - Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Applied Computer Science (programme FPF, B1802 AplI)
- Applied Mathematics (programme MU, B1101)
- Applied Mathematics in Risk Management (programme MU, B1101)
- Information studies with the focus on library science (programme FPF, B7201 InSK)
- Computer Science and Technology (programme FPF, B1801 Inf)
- Mathematical Methods in Economics (programme MU, B1101)
- Mathematics (programme MU, B1101)
- Computer Technology and its Applications (programme FPF, B1702 AplF)
- Course objectives
- The course provides a basic overview of goals, methods and techniques of the contemporary artificial intelligence (AI). The explanation is centered at the view of an intelligent agent which perceives and acts in a certain environment. Due to restricted scope of the course we focus on rational behaviour of the agent, i.e., how to reach its goals most efficiently. Both agents' capabilities and properties of the environment must be considered. An introduction to rational agents construction is followed by techniques of the state space search, including a multi-agent environment and basic game strategies. The course is concluded by basics of machine learning, including artificial neural networks.
- Syllabus
- 1. Introduction, history,artificial intelligence evaluation and applications.
2. Intelligent agents: reactivity and deliberation, the subsumption architecture, model-based agents.
3. State space search, informed and uninformed strategies, heuristic functions.
4. Local and online search.
5. Constraints satisfaction problems and search.
6. State space in games, strategies and adversarial search.
7. Knowledge representation for intelligent agents.
8. Basics of machine learning, decision trees, regression.
9. Artificial neural networks.
10. Advanced AI topics - an overview.
- 1. Introduction, history,artificial intelligence evaluation and applications.
- Literature
- recommended literature
- MAŘÍK, V., ŠTĚPÁNKOVÁ, O., LAŽANSKÝ, J. a kol. Umělá inteligence 1-6. Academia, Praha, 2013. ISBN 80-200-0496-3. info
- RUSSELL, S.J., NORVIG, P. Artificial Intelligence: A Modern Approach (3rd Ed.). Prentice Hall, 2010. ISBN 978-0-13-604259-4. URL info
- KELEMEN, J. a kol. Základy umelej inteligencie. Bratislava, ALFA, 1992. info
- Teaching methods
- Interactive lecture
Lecture with a video analysis - Assessment methods
- Exam
- Language of instruction
- Czech
- Further comments (probably available only in Czech)
- Study Materials
The course can also be completed outside the examination period.
- Enrolment Statistics (recent)
- Permalink: https://is.slu.cz/course/fpf/summer2023/UIN1009