Balancing Population- and Individual-Level Adaptation in Changing Environments

Abstract

This article examines the interdependency of population-level adaptation (evolution) and individual-level adaptation (learning). More specifically, we assume a trade-off between the two means of adaptation, that is, a higher individual-level adaptation can only be achieved with a reduced population level adaptation and vice versa. This trade-off is apparent in computational evolutionary systems, and there is also evidence that it exists in nature. As we show, despite this considered trade-off, there exist environments in which a combined adaptation scheme is optimal. Furthermore, we demonstrate that the optimal adaptive behavior produced by a particular distribution of population- and individual-level adaptation depends on the environmental dynamics. Finally, we verify that the optimal balance (i.e., an optimal learning effort) can emerge from evolution when there is a trade-off between reproduction and lifetime.