The Less Intelligent the Elements, the More Intelligent the Whole. Or, Possibly Not?

We approach the debate on how ''intelligent'' artificial agents should be, by endowing the preys and predators of the Lotka-Volterra model with behavioral algorithms characterized by different levels of sophistication. We find that by endowing both preys and predators with the capability of making predictions based on linear extrapolation a novel sort of dynamic equilibrium appears, where both species co-exist while both populations grow indefinitely. While we confirm that, in general, simple agents favor the emergence of complex collective behavior, we also suggest that the capability of individuals to take first-order derivatives of one other's behavior may allow the collective computation of derivatives of any order.