one would still expect the parameters and properties of those algorithms to be at least partially genetically tuned towards the kinds of learning tasks that were most useful in the EEA

Compare jacob_cannell's earlier point that

obviously for any set of optimization criteria, constraints (including computational), and dataset there naturally can only ever be a single optimal solution (emphasis added)

Do we know or can we reasonably infer what those optimization criteria were like, so that we can implement them into our AI? If not, how likely and by how much would we expect the optimal solution to change?