Relative to this baseline of traditional differences as an evolutionary byproduct, we showed in previous work that SE and OL can readily evolve because they enhance the level of foraging efficiency . Here we show that the evolution of such increased optimization need not generate greater traditional differences between groups, but could instead reduce them (Fig. 3 a). It is intuitive to assume that more accurate SLMs will increase within-group similarity (or conformity) and hence increase differences between groups . However, this overlooks the effect of SLMs on enhancing repertoire optimization . If all groups are able to correctly identify and eat the highest quality resources then behavioral repertoires will become similar , because the highest quality resources are always a limiting subset (Fig. 1 d). Despite this possible convergence between groups, we find that even when learning parameters evolve, optimization can still be sufficiently limited to allow for traditional differences.