Introduction to Computational Intelligence

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

Winter term 2021/22

Prof. Dr. Günter Rudolph



Dates:    
Wednesday 10:15 - 11:45 am in lecture hall E23 (OH14)
First Lecture: Wednesday, 13-Oct-2021

Link to Moodle


News:


Tutorial: Marius Bommert (M.Sc.), Florian Wellner, LS 11

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  
13.10.2021 Fuzzy Systems I  
20.10.2021 Fuzzy Systems II  
27.10.2021 Fuzzy Systems III  
03.11.2021 Fuzzy Systems IV  
10.11.2021 Fuzzy Systems V  
17.11.2021 Evolutionary Algorithms I  
24.11.2021 Evolutionary Algorithms II  
01.12.2021 Evolutionary Algorithms III  
08.12.2021 Evolutionary Algorithms IV  
15.12.2021 Neural Networks I  
22.12.2021 Neural Networks II  
12.01.2022 Neural Networks III  
19.01.2022 Neural Networks IV  
26.01.2022 Neural Networks V  
02.02.2022 Swarm Intelligence  

Literature: