Lehrinhalte
theory of biological evolution, introduction to genetics, population genetics, population growth, evolutionary algorithms, applications, DNA computing, artificial life, theory of evolutionary algorithms, optimization algorithms, multi-objective optimization, meta models, co-evolution, genetic coding, representations of evolutionary algorithms, developmental processes, self-adaptation
Literature
[list]
[*]D.J. Futuyama: Evolutionary Biology. W. Henning, Genetik, Springer Verlag
[*]D.B. Fogel: Evolutionary Computation, IEEE Press
[*]I. Rechenberg: Evolutionsstrategie 94
[*]H.-P. Schwefel: Evolution and Optimum Seeking
[/list]
Voraussetzungen
Introductory courses mathematics. Basic computer skills.
theory of biological evolution, introduction to genetics, population genetics, population growth, evolutionary algorithms, applications, DNA computing, artificial life, theory of evolutionary algorithms, optimization algorithms, multi-objective optimization, meta models, co-evolution, genetic coding, representations of evolutionary algorithms, developmental processes, self-adaptation
Literature
[list]
[*]D.J. Futuyama: Evolutionary Biology. W. Henning, Genetik, Springer Verlag
[*]D.B. Fogel: Evolutionary Computation, IEEE Press
[*]I. Rechenberg: Evolutionsstrategie 94
[*]H.-P. Schwefel: Evolution and Optimum Seeking
[/list]
Voraussetzungen
Introductory courses mathematics. Basic computer skills.
- Lehrende: Bernhard Sendhoff
Semester: ST 2022