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em SAPIENTIA - Universidade do Algarve - Portugal


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An experimental study aimed at assessing the influence of redundancy and neutrality on the performance of an (1+1)-ES evolution strategy modeled using Markov chains and applied to NK fitness landscapes is presented. For the study, two families of redundant binary representations, one non-neutral family which is based on linear transformations and that allows the phenotypic neighborhoods to be designed in a simple and effective way, and the neutral family based on the mathematical formulation of error control codes are used. The results indicate whether redundancy or neutrality affects more strongly the behavior of the algorithm used.