  Human culture is uniquely cumulative and open-ended. Using a computational
model of cultural evolution in which neural network based agents evolve ideas
for actions through invention and imitation, we tested the hypothesis that this
is due to the capacity for recursive recall. We compared runs in which agents
were limited to single-step actions to runs in which they used recursive recall
to chain simple actions into complex ones. Chaining resulted in higher cultural
diversity, open-ended generation of novelty, and no ceiling on the mean fitness
of actions. Both chaining and no-chaining runs exhibited convergence on optimal
actions, but without chaining this set was static while with chaining it was
ever-changing. Chaining increased the ability to capitalize on the capacity for
learning. These findings show that the recursive recall hypothesis provides a
computationally plausible explanation of why humans alone have evolved the
cultural means to transform this planet.
