FPF:UIN1009 Artificial Intelligence - Course Information
UIN1009 Artificial Intelligence
Faculty of Philosophy and Science in OpavaSummer 2019
- 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 - Prerequisites (in Czech)
- 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
- Noted in artificial intelligence.
- Syllabus
- 1. Introduction, history, and the Turing test.
2. Reactivity and deliberation, the subsumption architecture.
3. Decentralization and communication.
4. Artificial neural networks.
5. From subsumption to deliberation (from Toto to MetaToto).
6. Knowledge and STRIPS.
7. The state space and the search procedures, types of heuristics.
8. The General Problem Solver.
9. The associative representation scheme. Example of computational learning.
10. The procedural representation scheme, and calling programs by goals.
11. The frame representation scheme. Default values and non-monotonicity.
12. Resume.
- 1. Introduction, history, and the Turing test.
- Literature
- required literature
- PFEIFER, R., SCHEIER, CH. Understanding Intelligence. The MIT Press, Cambridge Mass, 1999. info
- recommended literature
- NÁVRAT, P. a kol. Umelá inteligencia. Bratislava: Slovenská technická univerzita, 2002. info
- BROOKS, R. A. Cambrian Intelligence. Cambridge: The MIT Press, 1999. info
- KELEMEN, J. Strojovia a agenty. Bratislava: Archa, 1994. info
- MAŘÍK, V., ŠTĚPÁNKOVÁ, O., LAŽANSKÝ, J. a kol. Umělá inteligence 1-5. Academia, Praha, 1993. info
- WINSTON, P. H. Artificial Intelligence. Reading Mass.: Addison-Wesley, 1992. 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)
- The course can also be completed outside the examination period.
- Teacher's information
- * 75% attendance in course, active participation
* success rate of 70 % from written test, 30 % oral exam
- Enrolment Statistics (Summer 2019, recent)
- Permalink: https://is.slu.cz/course/fpf/summer2019/UIN1009