Artificial intelligence

Course guarantor:

Lecturer:

Tutor:

Supervisor:

Department of Applied Mathematics

Synopsis:

The course covers search and inference algorithms in major formal paradigms used in artificial intelligence such as logic theories, constraint programming and automated planning. The main principles and practical applications of discussed techniques will be illustrated.

Requirements:

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.

Note:

Further information:

https://courses.fit.cvut.cz/MI-UMI/

No time-table has been prepared for this course

The course is a part of the following study plans:

• Quantum Informatics (elective course)
• Mgr. programe Applied informatics (code ANIE) for the phase of study without specialization (elective course)
• Master specialization Embedded systems (elective course)
• Master specialization Business Informatics, 2026 (elective course)
• Master specialization Software Engineering (elective course)
• Master specialization Web Engineering (elective course)
• Master specialization Visual computing and Game design (elective course)
• Master specialization Computer Security, in Czech, 2026 (VO)
• Master specialization Computer Systems and Networks, in Czech, 2026 (VO)
• Master specialization Computer Science, in Czech, 2026 (VO)
• Master specialization Programming Languages, in Czech, 2026 (VO)
• Master specialization Artificial Intelligence, in Czech, 2026 (PS)
• Master programme, for the phase of study without specialisation, ver. for 2026 and higher (VO)