SubjectsSubjects(version: 953)
Course, academic year 2023/2024
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Seminar on Artificial Intelligence 2 - NAIL052
Title: Seminář z umělé inteligence 2
Guaranteed by: Department of Theoretical Computer Science and Mathematical Logic (32-KTIML)
Faculty: Faculty of Mathematics and Physics
Actual: from 2021
Semester: summer
E-Credits: 2
Hours per week, examination: summer s.:0/2, C [HT]
Capacity: unlimited
Min. number of students: unlimited
4EU+: no
Virtual mobility / capacity: no
State of the course: taught
Language: Czech, English
Teaching methods: full-time
Teaching methods: full-time
Additional information:
Guarantor: prof. RNDr. Roman Barták, Ph.D.
Class: Informatika Mgr. - volitelný
Classification: Informatics > Theoretical Computer Science
Is incompatible with: NAIX052
Is interchangeable with: NAIX052
Annotation -
Referative seminar about actual theoretical and practical questions in a field of Artificial Intelligence, based on published papers.
Last update: T_KTI (27.09.2002)
Aim of the course -

Using the form of oral presentations, the seminar teaches students how to watch recent results in AI and how present research results or alternatively how to solve some AI problems.

Last update: Barták Roman, prof. RNDr., Ph.D. (06.10.2017)
Course completion requirements -

Credit is given for presentation of a student and active participation at seminars (at least 80% seminars attended). After approval from the teacher and in special cases only, the presentation and attendance can be substituted by a written report. The credit cannot be repeated.

Last update: Barták Roman, prof. RNDr., Ph.D. (28.04.2020)
Literature -

Conference Proceedings

  • AAAI Conference on Artificial Intelligence
  • International Joint Conference on Artificial Intelligence
  • European Conference on Artificial Intelligence


  • Artificial Intelligence
  • Journal of Artificial Intelligence Research
Last update: Barták Roman, prof. RNDr., Ph.D. (06.10.2017)
Teaching methods -

Seminar with oral reports, where students present own results or results from literature. It may involve solving a selected AI problem.

Last update: Barták Roman, prof. RNDr., Ph.D. (06.10.2017)
Syllabus -

Topic of relevant papers and discussion topics:

Knowledge representation, knowledge engineering.

Constraint satisfaction, inference techniques.

Problem solving, games, automated planning.

Machine learning, agent-based systems.

Applications of AI.

Last update: T_KTI (06.05.2010)
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