Introduction to Computational Intelligence

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

Winter term 2024/25

Prof. Dr. Günter Rudolph



Dates:    
Wednesday 10:15 - 11:45 am in lecture hall E23 (OH14)
First Lecture: Wednesday, 09-Oct-2024

Link to Moodle


News:


Tutorial: Dr.-Ing. Marco Pleines, Jonas Kramer (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  
09.10.2024 Fuzzy Systems I  
16.10.2024 Fuzzy Systems II  
23.10.2024 Fuzzy Systems III  
30.10.2024 Fuzzy Systems IV  
06.11.2024 Fuzzy Systems V  
13.11.2024 Evolutionary Algorithms I  
20.11.2024 Evolutionary Algorithms II  
27.11.2024 Evolutionary Algorithms III  
04.12.2024 Evolutionary Algorithms IV  
11.12.2024 Neural Networks I  
17.12.2024 Neural Networks II  
08.01.2025 Neural Networks III   slide 17 supplemented
15.01.2025 Neural Networks IV  
22.01.2025 Neural Networks V  

Literature: