Learning outcomes of the course unit:
The goal of the subject is to obtain knowledge and skills in modern methods of modeling, control and optimization by using knowledge engineering, fuzzy systems, genetic algorithms and neural networks.
 
Course contents:
1. Introduction. Relationship between ICM and control theory.
2. Artificial intelligence.
3. Problems solution by inteligent methods.
4. General problems solvers (GPS, STRIPS, ...).
5. Expert systems.
6. Knowledge engineering.
7. Uncertainty in decision making.
8. Fuzzy systems and fuzzy control.
9. Knowledge-based control.
10. Genetic algorithms.
11. GA in control.
12. Neural networks. Basics. Learning. Deep learning.
13. NN applications in control.

Type of methodology: Combination of lecture and hands-on

Participants receive the certificate of attendance: Yes

Paid training activity for participants: No, it's free of charge

Participants prerequisite knowledge: Machine/Deep Learning concepts Numerical methods (linear algebra, statistics)