- Teacher: Gabriela Varvara
Almost all dynamical systems are, to some extent, non-linear. Whereas in the curriculum for undergraduate studies such non-linearities have been ignored, the course Nonlinear Dynamics focuses on the effects that non-linearities have in such systems.
This course has two main objectives: 1) to provide the mathematical fundamentals for reasoning about stability and control of nonlinear systems in a formal way, and 2) to provide numerical tools for analyzing the stability of nonlinear systems and for designing nonlinear controllers. The content will be mathematical with illustrative examples taken from general engineering systems (from mechanical, electrical, chemical and aeronautical engineering, as well as from bioengineering and finance).
- Teacher: Mihaela Hanako Matcovschi
This course aims at providing the understanding of artificial intelligence symbolic approach, by presenting both knowledge representation and reasoning aspects. On the knowledge representation side it mixes logical and production systems based representations. On the inference side it discusses decision making by means of logical languages (with a focus on resolution based reasoning) and the inference possibilities offered by forward chaining (data-driven) rule-based programming. Students should be able to formalize knowledge and use automated reasoning methods in order to develop knowledge based systems adapted to specific applications.
- Teacher: Doru Adrian Panescu