Department of Computer Science
Chair of Algorithm Engineering (Ls11)
Home Contact Deutsch English
Günter Rudolph: Lecture Introduction to Computational Intelligence (WS 2017/18)

Introduction to Computational Intelligence

(Wahlmodul INF-BSc-305 / AR-MSc-306)

Winter term 2017/18

Prof. Dr. Günter Rudolph

Wednesday 10:15 - 11:45 am Campus North, OH12, E.003
First Lecture: Wednesday, 11-OCT-2017


  • 1st Exam Date: Friday, 16-Feb-2018, 3:15 - 4:45 pm
    Results: download (version: 27-Feb-2018); Grading System: download
    Post-exam Review: Wednesday, 28-Feb-2018, 4:00 - 5:00 pm. Room: OH 14, R. 202.

  • 2nd Exam Date: Friday, 06-Apr-2018, 2:45 - 4:15 pm
    Results: download (version: 23-Apr-2018); Grading System: download
    Post-exam Review: Monday, 07-May-2018, 5:00 - 6:00 pm. Room: OH 14, R. 202.

Tutorial: Vanessa Volz (M.Sc.), LS 11 (web pages)

Instruction Language: English.
For a German version of this web page please click the 'Deutsch' button at the top right corner.

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, Hopfield nets, supervised and unsupervised learning, backpropagation.
Foundations of FS: Fuzzy sets, fuzzy numbers, fuzzy logic, fuzzy reasoning.
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.

11.10.17 Artificial Neural Networks I  
18.10.17 Artificial Neural Networks II  
25.10.17 Artificial Neural Networks III  
08.11.17 Artificial Neural Networks IV   (slide #5 corrected)
15.11.17 Fuzzy Systems I  
22.11.17 Fuzzy Systems II  
29.11.17 Fuzzy Systems III  
06.12.17 Fuzzy Systems IV  
13.12.17 Fuzzy Systems V  
20.12.17 Evolutionary Algorithms I  
10.01.18 Evolutionary Algorithms II  
17.01.18 Evolutionary Algorithms III  
24.01.18 Evolutionary Algorithms IV  
31.01.18 Swarm Intelligence  

  • A.E. Eiben and J.E. Smith: Introduction to Evolutionary Algorithms. Corrected 2nd printing. Springer 2007.
  • Raul Rojas: Neural Networks - A Systematic Introduction. Springer 1996. Available online.
  • G.J. Klir und B. Yuan: Fuzzy Sets and Fuzzy Logic. Prentice Hall 1995.
  • F. Höppner, F. Klawonn, R. Kruse und T. Runkler: Fuzzy Cluster Analysis. Wiley 1999.
  • Amit Konar: Computational Intelligence: Principles, Techniques and Applications. Springer 2005.

The university does not accept liability for the contents of linked external internet sites