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.

翻译：群体在个体能够从他人成功中学习时能更有效地协调。然而，获取此类知识并不总是容易，尤其是在现实环境中成功常被隐藏于公众视野之外。我们认为，社会推理能力可能有助于弥合这一差距，使个体能够通过可观察的行为轨迹更新对他人潜在知识与成功的信念。我们通过三项关于人类在集体感知任务中的行为研究，将我们的社会推理模型与更简单的启发式策略进行了比较。在实验1中，我们发现平均绩效随群体规模增加而提升的幅度超过非推理模型的预测。实验2引入了人工代理以评估个体如何有选择地依赖社会信息。实验3将这些发现推广到更复杂的奖励景观中。综合来看，我们的发现揭示了个体社会认知与集体行为灵活性之间的关系。