Artificial intelligence

The course is not on the list Without time-table
Code Completion Credits Range Language
MI-UMI Z,ZK 5 2P+1C Czech
Garant předmětu:
Department of Applied Mathematics

The subject deals in depth with modern approaches and algorithms used in contemporary artificial intelligence. Students will be introduced to advanced problem-solving techniques based on search and inference. A comprehensive overview of formal systems for problem modeling, related solving algorithms, and their practical applications will be presented. Emphasis will be placed on logical reasoning in artificial intelligence, which provides various guarantees, such as the completeness of the decision process or the precise justification of the decision. The lecture is based on the classical textbook of artificial intelligence [1]. The extra material on satisfiability, constraint programming, automated planning and robotics can be found in specialized textbooks [2], [3], [4], and [6]. Czech textbooks [5] are a suitable study material for the lecture as well.


Background from BI-ZUM: Fundamentals of Artificial Intelligence is assumed.

Syllabus of lectures:

1. Solving problems by searching

2. Constraint satisfaction [2]

3. Consistency techniques in constraint satisfaction [2]

4. Propositional satisfiability (SAT) [4]

5. Decision making in logical theories [4]

6. Automated planning [3]

7. Problem modeling

8. Reasoning in first order logic

9. Knowledge representation

10. Reasoning under uncertainty

11. Decision making in games

12. Robotics [6]

Syllabus of tutorials:

1. Search

2. Constraint programming

3. Satisfiability

4. Planning

5. Problem modeling

6. Games

Study Objective:

The aim of the course is to provide students with a deeper insight into modern areas of artificial intelligence related to problem solving. To show in detail selected important algorithms and methods. Lead the students to further independent study of problems in artificial intelligence.

Study materials:

[1] Russel, S., Norvig, P.: Artificial Intelligence: A Modern Approach (3rd Edition), Prentice Hall, 2009.

[2] Decher, R.: Constraint Processing, Morgan Kaufmann, 2003.

[3] Ghallab, M., Nau, D., Traverso, P.: Automated Planning and Acting, Cambridge University Press, 2016.

[4] Biere, A., Heule, M., Van Maaren, H., Walsh, T.: Handbook of Satisfiability, IOS Press, 2009.

[5] Lažanský, J., Mařík, V., Štěpánková, O., a kolektiv: Umělá inteligence (1) - (6), Academia, 2000 - 2013.

[6] LaValle, S.: Planning Algorithms / Motion Planning. Cambridge University Press, 2006.

Further information:
No time-table has been prepared for this course
The course is a part of the following study plans:
Data valid to 2024-07-21
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