The course is for 3rd year undergraduates and graduate students of CS. We will mostly study the problem of reasoning in presence of uncertainty. Different approaches to this problem are considered: Certainty Factor calculation, Probabilistic approach, Dempster-Shafer theory of evidence, Fuzzy Logic etc. In this connection different aspects of Learning Theory are discussed. In the last part the new development connected with these problems: Knowledge Discovery in Databases is considered.

Course plan:

Assignements: 6 homeworks with exercises. At the end of the course the students should pass exams in the form of a special homework (during three days). The final mark is mostly based on the result of this final homework. The results of mentioned 6 homeworks also have an influence on the final mark.

Requirements: Standard courses on Mathematics (Probability and Statistics, Linear Algebra, Infi).


P.H. Winston, Artificial Intelligence, Addison-Wesley, 1984.

J. Pearl, Probabilistic Reasoning in Intelligent Systems, Morgan Kaufmann, 1988.

A.Kandel, Fuzzy Expert Systems, CRC Press, 1991.

Editors: U.M. Fayyad et others, Advances in Knowledge Discovery and Data Mining, AAAI Press/The MIT Press, 1996.