内容简介：

In this talk we introduce models of learning processes in teams of individuals who collectively execute a sequence of tasks and whose actions are determined by individual skill levels and networks of interpersonal appraisals and influence. First, we propose and study three closely-related models, with increasing complexity, starting with a centralized manager-based assignment and learning model, and finishing with a social model of interpersonal appraisal, assignments, learning, and influences. We show how rational optimal behavior arises along the task sequence for each model, and discuss conditions of sub-optimality. Second, we briefly introduce some ongoing further interdisciplinary studies on collective learning, including novel models with more degrees of freedom, collective learning with noise and memory, and human-subject experimental protocols. Our work builds insightful connections among replicator dynamics from evolutionary games, influence networks from mathematical sociology, and transactive memory systems from organization science.

报告人简介：

Wenjun Mei received the B.Sc. degree in Theoretical and Applied Mechanics from Peking University, and the Ph.D. degree in Mechanical Engineering from University of California, Santa Barbara. He will be a postdoctoral researcher at ETH Zurich from May 2018. His current research interests include dynamics of network systems, mathematical sociology, network games and evolutionary dynamics.