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Last update: Mgr. Roman Neruda, CSc. (02.05.2006)
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Last update: T_KTI (26.05.2008)
Naučit základní techniky používané v evolučních algoritmech. Ukázat souvislosti s příbuznými oblastmi dataminingu a učení. |
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Last update: Mgr. Roman Neruda, CSc. (02.05.2006)
Mitchell, M.: Introduction to genetic algorithms. MIT Press, 1996.
Goldberg, D.: Genetic algorithms in search optimization and machine learning, Addison-Wesley, 1989.
Holland, J.: Adaptation in natural and artificial systems, MIT Press, 1992 (2nd ed).
Holland, J.: Hidden order, Addison-Wesley, 1995. |
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Last update: Mgr. Roman Neruda, CSc. (02.05.2006)
Models of evolution, basic approaches and notions. Population, recombination, fitness evaluation.
Genetic algorithms, solution encoding in a chromozome, basic operators of selection, mutation, crossover.
Selection, objective function, dynamic vs. static, roulette-wheel selection, tournaments, elitism.
Schema theorem, building block hypotheses, implicit paralallelism.
Probabilistic models of simple genetic algorithm, finite and infinite population.
Machine learning and data mining, evoluion of expert systems, internal representation, Michigan vs. Pittsburg approach.
Clasifier systems, if-then rules, bucket brigade algorithm, Q-learning, production systems. |