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.