  Groups coordinate more effectively when individuals are able to learn from
others' successes. But acquiring such knowledge is not always easy, especially
in real-world environments where success is hidden from public view. We suggest
that social inference capacities may help bridge this gap, allowing individuals
to update their beliefs about others' underlying knowledge and success from
observable trajectories of behavior. We compared our social inference model
against simpler heuristics in three studies of human behavior in a collective
sensing task. In Experiment 1, we found that average performance improves as a
function of group size at a rate greater than predicted by non-inferential
models. Experiment 2 introduced artificial agents to evaluate how individuals
selectively rely on social information. Experiment 3 generalized these findings
to a more complex reward landscape. Taken together, our findings provide
insight into the relationship between individual social cognition and the
flexibility of collective behavior.
