Title: Robust Social Learning from Unordered Actions (Joint work with Li Guo, Xiao Lin and Penghuan Yan)

Speaker: 何斯超，Kevin He, Assistant Professor at the University of Pennsylvania, Department of Economics

Abstract: People often learn from others’ actions without observing the chronology of who influenced whom. We study a sequential social-learning model where agents observe predecessors’ actions as an unordered set and minimize worst-case expected loss across move orders. The unique equilibrium with this robust decision criterion is DeGroot aggregation: each agent equally averages their private signal and all previous actions. Robust actions are disproportionately influenced by early signals and converge to a random consensus centered around the true state. By contrast, Bayesian agents in the same environment learn the state, as does a Bayesian observer who sees the unordered actions of robust agents.

时间：2026年9月18日  15:30-17:00

地点：复旦大学人妻 601会议室