Günter Rudolph: Lecture Introduction to Computational Intelligence (WS 2024/25)
| Dates: |
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| Wednesday |
10:15 - 11:45 am |
in lecture hall E23 (OH14)
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| First Lecture: |
Wednesday, 09-Oct-2024 |
News:
- 13-Jan-2025
The registration to the exams must be made via BOSS
for the study programs BSc Informatik and MSc Automation & Robotics,
whereas students of MSc Data Science must use the new
Campusportal.
All other study programs must register (exam date, name, matriculation number, study program)
by an email sent to Prof. Rudolph. Registration is open now.
Important: You cannot participate in the exam without due registration. The registration deadline is 7 days prior to the exam.
ATTENTION: In the department of Computer Science you may de-register up to one week prior to the exam.
Notice: Currently, registration is possible without formal eligibility (Studienleistung). But we will scrutinize if you are approved or not.
In the end, we'll get you! ;-)
- 29-Oct-2024
The written exams will take place on
| - Tuesday, | 04-Feb-2025, | 4:00pm - 5:30pm |
| - Friday, | 04-Apr-2025, | 1:00pm - 2:30pm |
- 29-Sep-2024
The module Computational Intelligence consists of a lecture and a tutorial, that is offered twice a week.
You will attend only one of the tutorials as they are identical.
It is not necessary to enroll to the lecture; simply come to the lecture hall E23 in building OH14 at the given date.
But you should register to the tutorial;
simply click on the link to moodle above and you will get further information about this issue.
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:
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Introduction and Organizational Issues |
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| 09.10.2024 |
Fuzzy Systems I |
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| 16.10.2024 |
Fuzzy Systems II |
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| 23.10.2024 |
Fuzzy Systems III |
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| 30.10.2024 |
Fuzzy Systems IV |
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| 06.11.2024 |
Fuzzy Systems V |
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| 13.11.2024 |
Evolutionary Algorithms I |
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| 20.11.2024 |
Evolutionary Algorithms II |
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| 27.11.2024 |
Evolutionary Algorithms III |
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| 04.12.2024 |
Evolutionary Algorithms IV |
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| 11.12.2024 |
Neural Networks I |
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| 17.12.2024 |
Neural Networks II |
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| 08.01.2025 |
Neural Networks III |
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slide 17 supplemented |
| 15.01.2025 |
Neural Networks IV |
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| 22.01.2025 |
Neural Networks V |
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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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