Representational capacity shapes both the "whether" and "how" of social learning.

Social learning is widely understood as offering a mechanism to mitigate the costs and risks of individual trial-and-error exploration. This cost-avoidance account implies a framing of social learning as a resource-rational adaptation, which should be most beneficial to populations with limited capacity to learn asocially. But in cases of peer-to-peer transmission, that same limited capacity may hinder the reliability of social information-rendering it less, not more, useful. So how do these conflicting intuitions resolve? Across a series of simulation experiments, we find evidence for an 'inverse-U' relationship where social information use emerges most strongly in populations with moderate capacity relative to the complexity of their environment. Furthermore, we demonstrate a co-evolutionary transition in social learning strategies: as population capacity rises, selection pressure shifts from favouring a success bias to a conformist approach. Our findings suggest that constraints on information-processing play an important role in the emergence of culture, determining not just if a species learns socially, but also how. All code for this project is available at https://github.com/maxtaylordavies/capacity-and-social-learning.