Artificial Intelligence I35051

Course content:
1. Introduction to artificial intelligence.
2. Notions: Data, information, knowledge and wisdom.
3. Methods of knowledge representation using rough sets - basic notions.
4. Methods of knowledge representation using rough sets - examples of applications.
5-6 Methods of decision rules generation.
7. From logic to reasoning.
8. Methods of knowledge representation using logic.
9. State space search methods.
10. Methods of artificial intelligence in data mining the Web.
11. Granular computing and data clustering methods.
12. Neural networks and decision rules.
13. Methods of knowledge representation using fuzzy sets.
14. Evolutionary algorithms.
15. Artificial Intelligence and Computational Intelligence.
Learning outcomes:
Ability to describe knowledge based on rough sets, fuzzy sets, neural networks, clustering algorithms, evolutionary algorithms and logic.