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Günter Rudolph: Lecture Introduction to Computational Intelligence (WS 2022/23)

Introduction to Computational Intelligence

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

Winter term 2022/23

Prof. Dr. Günter Rudolph



Dates:    
Wednesday 10:15 - 11:45 am in lecture hall E23 (OH14)
First Lecture: Wednesday, 12-Oct-2022

Link to Moodle


News:
  • Published 30-Nov-2022
    Backed by overwhelming majority of votes, the lecture in the last week prior to Christmas (21-Dec-2022) will be presented in online mode via Zoom (no hybrid mode!). The link will appear in Moodle in due time.
  • Published 18-Oct-2022 (updated 29-Nov-2022)
    The written exams will take place on
    - Tuesday,07-Feb-2023,6:00pm - 7:30pm.confirmed!
    - Wednesday, 29-Mar-2023,9:00am - 10:30am.confirmed!
    The exams are planned to be run in presence (on-site / in classroom).
    Information about registration will follow in due time.


Tutorial: Marius Bommert (M.Sc.), Alexander van der Staay (B.Sc.), Gero Grühn (cand. 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  
12.10.2022 Fuzzy Systems I  
19.10.2022 Fuzzy Systems II  
26.10.2022 Fuzzy Systems III  
02.11.2022 Fuzzy Systems IV  
09.11.2022 Evolutionary Algorithms I  
16.11.2022 Evolutionary Algorithms II  
23.11.2022 Evolutionary Algorithms III  
30.11.2022 Evolutionary Algorithms IV  

Literature:
  • 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.
  • Ian Goodfellow, Yoshua Bengio, and Aaron Courville: Deep Learning. MIT Press 2017.
  • 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.



 
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