  Social learning, copying other's behavior without actual experience, offers a
cost-effective means of knowledge acquisition. However, it raises the
fundamental question of which individuals have reliable information: successful
individuals versus the majority. The former and the latter are known
respectively as success-based and conformist social learning strategies. We
show here that while the success-based strategy fully exploits the benign
environment of low uncertainly, it fails in uncertain environments. On the
other hand, the conformist strategy can effectively mitigate this adverse
effect. Based on these findings, we hypothesized that meta-control of
individual and social learning strategies provides effective and
sample-efficient learning in volatile and uncertain environments. Simulations
on a set of environments with various levels of volatility and uncertainty
confirmed our hypothesis. The results imply that meta-control of social
learning affords agents the leverage to resolve environmental uncertainty with
minimal exploration cost, by exploiting others' learning as an external
knowledge base.
