Information on individual educational components (ECTS-Course descriptions) per semester

  
Degree programme:Master Computer Science
Type of degree:FH Master´s Degree Programme
 Full-time
 Summer Semester 2023
  

Course unit titleEvolutionary Algorithms and Optimization
Course unit code024913020506
Language of instructionEnglish
Type of course unit (compulsory, optional)Elective
Semester when the course unit is deliveredSummer Semester 2023
Teaching hours per week2
Year of study2023
Level of course unit (e.g. first, second or third cycle)Second Cycle (Master)
Number of ECTS credits allocated3
Name of lecturer(s)Hans-Georg BEYER


Prerequisites and co-requisites

LV 024913010503 Artificial Intelligence; Nonlinear Optimization, Linear Algebra, Analysis, Probability Theory and Statistics

Course content
  • (1+1) evolution strategy (ES) and 1/5 rule
  • Simulated annealing
  • Multi-Membered ES
  • Self-adaptation
  • Cumulative step size adaptation
  • Matrixadaptation-ES
  • Empirical evaluation of black box search algorithms
  • Introduction into progress rate and runtime analysis
  • Genetic Algorithms
  • Genetic Programming
Learning outcomes

The students

  • are acquainted with basic methods and algorithms from the field of evolutionary learning and optimization.
  • can apply and evaluate these algorithms and methods.
  • are able to understand research papers in this field.
Planned learning activities and teaching methods

Lecture, laboratory exercises, literature work and seminar presentation if appropriate

Assessment methods and criteria

Final exam character with an oral exam. Providing the laboratory exercises are prerequisites for the oral exam.

Comment

None

Recommended or required reading

Use of Octave/MatLab.

  • Beyer, Hans-Georg (2010): The Theory of Evolution Strategies. Softcover reprint of hardcover 1st ed. 2001 Edition. Berlin Heidelberg: Springer. Available at: URL: http://link.springer.com/10.1007/978-3-662-04378-3 (Accessed on: 21 December 2021).
  • Eiben, A.E; Smith, James E (2015): Introduction to Evolutionary Computing. Available at: URL: https://doi.org/10.1007/978-3-662-44874-8 (Accessed on: 21 December 2021).
  • Engelbrecht, Andries P. (2007): Computational Intelligence: An Introduction. 2nd Ed. Chichester, England ; Hoboken, NJ: Wiley.
  • Weicker, Karsten (2015): Evolutionäre Algorithmen. 3., überarb. u. erw. Aufl. 2015 Edition. Wiesbaden: Springer Vieweg
Mode of delivery (face-to-face, distance learning)

Face-to-face event with recording of the lecture

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