Abstract
An investigation of the role of the genotype–phenotype mapping (G-Pm) is presented for an evolutionary optimization task. A simple genetic algorithm (SGA) plus a mapping creates a new mapping genetic algorithm (MGA) that is used to optimize a Boolean decision tree for an information retrieval task, with the tree being created via a relatively complex mapping. Its performance is contrasted with that of a genetic programming algorithm, British Telecom Genetic Programming (BTGP) which operates directly on phenotypic trees. The mapping is observed to play an important role in the time evolution of the system allowing the MGA to achieve better results than the BTGP. We conclude that an appropriate G-Pm can improve the evolvability of evolutionary algorithms.
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