| Abstract: |  This thesis is aimed at the research of evolutionary algorithms combining a modern approach in evolutionary computing called novelty search with classical approach based on fitness optimization. In the thesis the novelty search is analysed along with one existing approach that already combines novelty search with fitness. Their advantages and disadvantages are discussed. Based on this analysis, there are proposed two new hybrid evolutionary algorithms based on the classical fitness-based approach and the novelty search. These two algorithms are tested, along with three other existing algorithms, on a series of experiments covering easy problems and very complex ones too. In the end of the thesis the results of the experiments are presented with the emphasis on comparing the two new hybrid algorithms with the existing ones.
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