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Lecturer(s)
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Brandejský Tomáš, doc. Ing. Dr.
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Course content
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Darwinian model of evolution, genetic algorithms and evlutoinary strategies, simulated anealing, diferential evolution, SOMA, genetic programming, symbolic regression
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Learning activities and teaching methods
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unspecified
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Learning outcomes
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Introductin into fundamental ideas of evolutionary techniques. Within the stude students may focus deeply into optimization techniques and related genetic algorithms and evolutionary strategies, simulated annealing and others; or to problems of structure development and symbolic regression and thus especially to genetic programming. In the study students have opportunity to test algorithmsin practice. In the subject there are also explained basic knowledge of information dynamics of GA, ES and GPA to allow students to apply these algorithms efficiently.
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Prerequisites
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unspecified
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Assessment methods and criteria
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unspecified
Except examination of theoretical principles introduced algorithms there is required ability to apply suitable evolutionary algorithm to given problem.
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Recommended literature
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Hynek, Josef. Genetické algoritmy a genetické programování. Praha: Grada, 2008. ISBN 978-80-247-2695-3.
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Koza, John R. Genetic programming III : Darwinian invention and problem solving. San Francisco: Morgan Kaufmann, 1999. ISBN 1-55860-543-6.
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