Limiting the number of niches in MAP-Elites is important to avoid dilution of the evolutionary pressure that guides the al-gorithm. To counter the exponential growth of the amount of niches, advanced implementations of MAP-Elites, including GB-EPI and GP-BI, make use of a centroidal Voronoi tessellation (CVT) instead of a regular grid, because it can cover a highdimensional space with a fixed and predefined number of niches regardless of the amount of properties used to span it. GB-EPI and GB-BI also make use of positional analogue scanning (structure modifications are applied in systematic batches by the mutation operator) and fitness function memoisation (keeping an on-thefly record of obtained results to ensures that an algorithm does not unnecessarily repeat expensive calculations) to increase their efficiency.