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Course, academic year 2023/2024
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Artificial Intelligence 1 - NAIL069
Title: Umělá inteligence 1
Guaranteed by: Department of Theoretical Computer Science and Mathematical Logic (32-KTIML)
Faculty: Faculty of Mathematics and Physics
Actual: from 2020
Semester: winter
E-Credits: 4
Hours per week, examination: winter s.:2/1, C+Ex [HT]
Capacity: unlimited
Min. number of students: unlimited
4EU+: no
Virtual mobility / capacity: no
State of the course: taught
Language: English, Czech
Teaching methods: full-time
Teaching methods: full-time
Additional information: http://ktiml.mff.cuni.cz/~bartak/ui/
Guarantor: prof. RNDr. Roman Barták, Ph.D.
Class: Informatika Mgr. - Teoretická informatika
Classification: Informatics > Theoretical Computer Science
Is incompatible with: NAIX069
Is interchangeable with: NAIX069
Annotation -
An introductory course on artificial intelligence with the focus on basic concepts and methods. The cources requires knowledge of logic at the level of undergraduate course.
Last update: Barták Roman, prof. RNDr., Ph.D. (10.05.2011)
Aim of the course -

The course gives an introduction to fundamental concepts and techniques of Artificial Intelligence. The students will learn several search techniques for problem solving, including informed search such as A* algorithm, methods of logical representation of knowledge, inference techniques, constraint satisfaction, and planning techniques.

Last update: BARTAK/MFF.CUNI.CZ (31.03.2008)
Course completion requirements -

To successfully complete the course, the student is required to do the exam and to get credit. The credit is not necessary for registration to exam. Credit is given for a given number of points (specified by a teacher at the beginning of semester) obtained for solving programming homework. Credit cannot be repeated.

Last update: Barták Roman, prof. RNDr., Ph.D. (04.05.2023)
Literature -

S. Russell, P. Norvig: Artificial Intelligence; A Modern Approach, 2003

V. Mařík, O. Štepánková, J. Lažanský a kol.: Umělá Inteligence, 1-6. Academia, Praha

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

lecture and practical exercise

Last update: Barták Roman, prof. RNDr., Ph.D. (06.10.2017)
Requirements to the exam -

The exam consists of a written preparation and an oral part. The requirements are given by the course syllabus.

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

Intelligent agents, environment, and structure of agents.

Problem solving by search (DFS, BFS, ID, A*, IDA*, local and on-line search, heuristics).

Constraint satisfaction.

Games (minimax, alfa-beta pruning).

Knowledge representation and inference techniques (forward and backward chaining, resolution).

Automated planning.

Last update: BARTAK/MFF.CUNI.CZ (18.02.2008)
 
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