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At the end of the module “Computational Intelligence” students are able to apply modern methods of artificial intelligence in general and to analyze specifically applications in the area of real-time control for technical systems.

Introduction to theory and application of neuronal networks, fuzzy control techniques, search- and exploration-based machine learning approaches for optimization, support-vector machines, statistical learning methods, evolutionary and genetic algorithms for optimization, reinforcement learning, distributed agent-based learning. Applications: Design of intelligent software modules for real-time control of engineered systems and sensory information processing.

Programmingknowledge in "C"

The assessment consists of a written exam (contributing 70%) and several individual programming assignments throughout the semester (contributing 30%). In the closed-book written exam students demonstrate acquired knowledge and transfer concepts and algorithms to similar problems. Some questions require own calculations and free text answers, other questions allow ticking multiple choice boxes. The problem related programming assignments throughout the semester evaluate the students’ abilities to implement algorithms introduced in the lecture in computer programs. The correct execution of algorithms is graded. Type of Assessment written Duration of Assessment 90

Arbeitsblättersammlung zur Vorlesung