UFPT501 Artificial Intelligence

Faculty of Philosophy and Science in Opava
Summer 2019
Extent and Intensity
2/0/0. 3 credit(s). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Jozef Kelemen, DrSc. (lecturer)
doc. Ing. Petr Sosík, Dr. (lecturer)
Guaranteed by
prof. RNDr. Jozef Kelemen, DrSc.
Centrum interdisciplinárních studií – Faculty of Philosophy and Science in Opava
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
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.
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
The course is also listed under the following terms Summer 2017, Summer 2018, Summer 2020, Summer 2021, Summer 2022, Summer 2023.
  • Enrolment Statistics (Summer 2019, recent)
  • Permalink: https://is.slu.cz/course/fpf/summer2019/UFPT501