摘要:

 In this talk, I will discuss models for the evolution of self and interpersonal appraisals, social power and interpersonal influences for a group of individuals. Specifically, I will propose models of team dynamics and learning in two scenarios: groups who discuss and form opinions along a sequence of issues, and group who execute a sequence of decomposable tasks.  In both scenarios we establish the emergence of rational optimal behavior, or lack thereof, as a result of the natural dynamical evolution of interpersonal appraisals and influence structures.  Our models and analysis results are grounded in multiagent network systems, influence networks from mathematical sociology, replicator dynamics from evolutionary games, and transactive memory systems from organization science.

报告人简介:  

Francesco Bullo is a Professor with the Mechanical Engineering Department and the Center for Control, Dynamical Systems and Computation at UC Santa Barbara.  He was previously associated with the University of Padova, the California Institute of Technology and the University of Illinois at Urbana-Champaign.  His main research interests are network systems and distributed control with application to robotic coordination, power grids and social networks.  He is the coauthor of "Geometric Control of Mechanical Systems" (Springer, 2004) and "Distributed Control of Robotic Networks" (Princeton, 2009).  His articles received the 2008 IEEE CSM Outstanding Paper Award, the 2010 Hugo Schuck Best Paper Award, the 2013 SIAG/CST Best Paper Prize, and the 2014 Automatica Best Paper Award.  He is currently serving as Chair of the Mechanical Engineering Department at UCSB and has served as Vice-President for Technical Activities and for Publications for the IEEE Control Systems Society.