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Course, academic year 2023/2024
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Seminar on Artificial Intelligence II - NAIX052
Title: Seminář z umělé inteligence II
Guaranteed by: Student Affairs Department (32-STUD)
Faculty: Faculty of Mathematics and Physics
Actual: from 2022
Semester: summer
E-Credits: 3
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
Teaching methods: full-time
Teaching methods: full-time
Is provided by: NAIL052
Guarantor: prof. RNDr. Roman Barták, Ph.D.
Class: Informatika Mgr. - volitelný
Classification: Informatics > Theoretical Computer Science
Pre-requisite : {NXXX038, NXXX039, NXXX040, NXXX067, NXXX069}
Incompatibility : NAIL052
Interchangeability : NAIL052
Annotation -
Last update: T_KTI (27.09.2002)
Referative seminar about actual theoretical and practical questions in a field of Artificial Intelligence, based on published papers.
Aim of the course -
Last update: prof. RNDr. Roman Barták, Ph.D. (06.10.2017)

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.

Course completion requirements -
Last update: prof. RNDr. Roman Barták, Ph.D. (28.04.2020)

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.

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

Conference Proceedings

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

Journals

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

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

Syllabus -
Last update: T_KTI (06.05.2010)

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.

 
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