Introduction to Computational Intelligence

(Elective Module INF-BSc-305 / AR-MSc-306)

Winter term 2025/26

Prof. Dr. Günter Rudolph



Dates:    
Wednesday 10:15 - 11:45 am OH14 - E23
First Lecture: Wednesday, 15-Oct-2025

Link to Moodle


News:


Tutorial: Andreas Roth (M.Sc.), N.N. (B.Sc.)

Instruction Language: English.


Description:
Typically, Computational Intelligence is used as an umbrella term for the fields of artificial neural nets (ANN), fuzzy systems (FS) and evolutionary computation (EC). This course offers a thorough introduction into all three fields.

Foundations of ANN: McCulloch-Pitts nets, perceptrons, RBF nets, Hopfield nets, convolutional neural nets (CNN), recurrent nets.
Foundations of FS: Fuzzy sets, fuzzy numbers, fuzzy logic, fuzzy reasoning, fuzzy control, fuzzy clustering.
Foundations of EC: Algorithmic basics, parameterization, analysis methods, limits of deployment.

Students should get an overview about the different aspects of Computational Intelligence. They should be familiar with the essential elements in all three fields (ANN, FS, EC) and able to deploy and adapt these methods for real applications. Moreover, they should be able to assess when to deploy these methods and when not.


Slides:
Introduction and Organizational Issues  
15.10.2025 Fuzzy Systems I  
22.10.2025 Fuzzy Systems II  
29.10.2025 Fuzzy Systems III  
05.11.2025 Fuzzy Systems IV  
12.11.2025 Fuzzy Systems V  
19.11.2025 Evolutionary Algorithms I  
26.11.2025 Evolutionary Algorithms II  

Literature: