Intelligent Systems

Computational Intelligence

teach

Lecture (infCI-01a)

4 SWS, ECTS Credits: 8
Language of instruction: german
Time: Monday 14:15-15:45 and Wednesday 10:15-11:45
Lecture period winter term 2021-2022: 18.10.2021 - 22.2.2022
For more information UnivIS or in Modulinformationsystem


Exercise (ÜinfCI-01a)

2 SWS
Language of instruction: german
Time: Wednesday 12:15-13:45
Lecture period winter term 2021-2022: 18.10.2021 - 22.2.2022
Fore more information UnivIS

 

Summary

The term "Computational Intelligence" (CI) describes a sub-area of ​​artificial intelligence. Essentially, it summarizes three biologically motivated areas of information processing: Based on algorithms of fuzzy logic and artificial neural networks as well as on evolutionary algorithms, the aim is to master complex systems and combine them with other, typically biologically-inspired, processes. Originally coined in the 1990s by the Institute of Electrical and Electronics Engineers (IEEE), the term is now often used synonymously with soft computing. All sub-areas included have in common that they make mechanisms of natural (i.e. in particular biological, physical or social) problem-solving strategies usable for mathematical or engineering-technical questions. The aim is not a direct transfer or "technical copy", but an understanding and imitation of the basic mechanisms. The methods developed in this way are in contrast to exact mathematical methods - one rather freely follows the motto: "What works is allowed".

 

Learning goals

The aim of the event is to provide an initial overview of the field of computational intelligence in theory and practice. Building on this, students should be given a basic understanding and appropriate approaches so that the following goals in particular can be achieved:

  • The students have a basic understanding of the complexity of technical systems and know how it can be mastered.
  • The students know how seemingly complex relationships can be easily described with mechanisms of computational intelligence.
  • Techniques from the field of Computational Intelligence / Soft Computing and their advantages and disadvantages in comparison are known.

 

Workload

60 hours of lectures, 30 hours of face-to-face exercises, 150 hours of self-study