We study a social learning scheme where at every time instant, each agent chooses to receive information from one of its neighbors at random. We show that under this sparser communication scheme, the agents learn the truth eventually and the asymptotic convergence rate remains the same as the standard algorithms which use more communication resources. We also derive large deviation estimates of the log-belief ratios for a special case where each agent replaces its belief with that of the chosen neighbor.

翻译：我们研究一个社会学习计划,每个代理商都选择随机接收来自其邻居的信息。我们显示,在这种稀疏的通信计划下,代理商最终会了解真相,而无药可治的趋同率与使用更多通信资源的标准算法相同。我们还得出了一个特殊案例的日志-信仰比率的巨大偏差估计,在这个特殊案例中,每个代理商用所选择的邻居的信仰取代自己的信仰。