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Günter Rudolph: Lecture Introduction to Computational Intelligence (WS 2009/10)

Introduction to Computational Intelligence

(Wahlmodul INF-BA-205 / MSc Automation and Robotics)

Winter term 2009/10

Prof. Dr. Günter Rudolph



Dates:    
Wednesday 10:15 - 12:00 OH 14 / R. E23
First Lecture: Wednesday, 14-OCT-2009


'Grade 4.0' vs. 'passed'

As of 5th August 2010 it is offcially confirmed that all participants from the Master's program Automation and Robotics who passed the tutorial will get a 'passed' instead of the 'grade 4.0' on their certificate. In case of any problem please contact me.


Tutorials: (web pages)
Optionally Wednesday or Thursday afternoon (16:15-17:00).


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

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, 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.


Slides:
14.10.09 Artificial Neural Networks I  
21.10.09 Artificial Neural Networks II  
28.10.09 Artificial Neural Networks III  
04.11.09 Artificial Neural Networks IV  
11.11.09 Fuzzy Systems I  
18.11.09 Fuzzy Systems II  
25.11.09 Fuzzy Systems III  
02.12.09 Fuzzy Systems IV  
16.12.09 Fuzzy Systems V   (to be delivered)
06.01.10 Evolutionary Algorithms I (Part A)  
Evolutionary Algorithms I (Part B)  
13.01.10 Evolutionary Algorithms II  
20.01.10 Evolutionary Algorithms III (Part A)  
Evolutionary Algorithms III (Part B)  

Literature:
  • Raul Rojas: Neural Networks - A Systematic Introduction. Spinger 1996. Available online.
  • G.J. Klir and B. Yuan: Fuzzy Sets and Fuzzy Logic. Prentice Hall 1995.
Will be extended shortly.



 
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