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Artificial Intelligence I - NAIX069

Title:	Umělá inteligence I
Guaranteed by:	Student Affairs Department (32-STUD)
Faculty:	Faculty of Mathematics and Physics
Actual:	from 2019
Semester:	winter
E-Credits:	5
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
Teaching methods:	full-time
Teaching methods:	full-time
Is provided by:	NAIL069
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
Pre-requisite :	{NXXX019, NXXX020, NXXX021, NXXX038, NXXX039, NXXX040, NXXX067, NXXX069}
Incompatibility :	NAIL069
Interchangeability :	NAIL069

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Annotation -

Last update: prof. RNDr. Roman Barták, Ph.D. (10.05.2011)

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.

Aim of the course -

Last update: BARTAK/MFF.CUNI.CZ (31.03.2008)

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.

Course completion requirements -

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

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.

Literature -

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

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

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

Teaching methods -

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

lecture and practical exercise

Requirements to the exam -

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

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

Syllabus -

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

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.