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Evolutionary programming, evolutionary strategies, genetic programming. Open-ended evolution and artificial life. Binary vs. float evolutionary algorithms, numerical optimization. Constraint handling, combinatorial optimization. Evolutionary learning of neural networks.
Last update: Neruda Roman, Mgr., CSc. (02.05.2006)
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TBA Last update: Hric Jan, RNDr. (07.06.2019)
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Oral exam Last update: Hric Jan, RNDr. (07.06.2019)
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Mitchell, M.: Introduction to genetic algorithms. MIT Press, 1996.
Michalewicz, Z: Genetic algorithms + data structures = evolutionary programs. Springer Verlag, 1994.
Koza, J.: Genetic programming (I,II,III) MIT Press, 1992, 1994, 1996.
Chambers, L. (ed.): Practical handbook of genetic algorithms, CRC Press, 1995. Last update: Pilát Martin, doc. Mgr., Ph.D. (04.11.2019)
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Evolutionary programming, finite automata, meta-evolution.
Evolution Strategie, cooperation of individuals, 1+1, m+1 algorithms.
Genetic programming, LISP tree reprezentations, modularity.
Open-ended evolution, adaptive behavior, artificial life simulations, emergence (Tierra, Avida, Framsticks)
Numerical optimization, binary vs. float reprezentations, constraints handling.
Combinatorial problems, knapsack, travelling salesman, representations, operators.
Neural networks evolution, internal representation, topology, weights learning, hybrid algorithms.
Last update: Neruda Roman, Mgr., CSc. (02.05.2006)
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