Abstract. In nature the genotype of many organisms exhibits
diploidy, i.e., it includes two copies of every gene. In this paper we describe
the results of simulations comparing the behavior of haploid and diploid
populations of ecological neural networks living in both fixed and changing
environments. We show that diploid genotypes create more variability in fitness
in the population than haploid genotypes and buffer better environmental change;
as a consequence, if one wants to obtain good results for both average and peak
fitness in a single population one should choose a diploid population with an
appropriate mutation rate. Some results of our simulations parallel biological
findings.