Models of evolution, genetic algorithms, representation and operators of selection, mutation and crossover. Problem solving by means of evolutionary computation. Theoretical properties of simple genetic algorithm. Schemata theorem and building block hypothesis, probabilistic models. Evolutionary machine learning, Michigan vs. Pittsburg approach, classifier systems.
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