Soft Computing

The Soft Computing course is given on the seventh semester of undergraduate studies.

Goal

Students will learn about concepts, techniques and selected examples of application of soft computing.

Outcome

The acquired knowledge is the basis for solving complex problems which require intelligence and cannot be solved using conventional mathematical approach.

Content

Main topics of the course:

Evolutionary computing: genetic algorithms, genetic programming, multiple intelligence, evolutionary strategies. Neural computing: neural networks. Machine learning: supervised learning, unsupervised learning, reinforcement learning. Fuzzy systems: fuzzy sets, fuzzy logic. Probabilistic reasoning: belief propagation, chaos theory.