October 28, 2022, ESB 2001

In this talk I want to address the scenario where a global controller, i.e. a “superplayer” or “central planner”, wishes to influence the group behavior of a multi-agent system. The superplayer broadcasts controls seen globally by the agents to encourage them to select actions that align with a global goal. This framework may describe phenomena appearing in social media, financial networks, and cyber-physical systems like power grids. In this talk I first characterize the capabilities of the superplayer given a basic Markov decision process (MDP) model by analyzing the reachability of control objectives and discussing policies that attain reachable objectives. This is extended with a discussion of cluster-based control schemes and efficient solution methods for cluster-based policies. By describing how the controller exerts influence on agents, a deeper understanding of the overall system may be achieved. For example, impactful agents may be identified by characterizing each agent’s potential to disrupt the superplayer’s objective. I will also discuss how the superplayer may prepare for emergency scenarios by evaluating the goodness of their policy under node dropouts. I will conclude by suggesting directions for future work.

Bruno Sinopoli is the Das Family Distinguished Professor at Washington University in St. Louis, where he is also the founding director of the center for Trustworthy AI in Cyber-Physical Systems and chair of the Electrical and Systems Engineering Department. He received the Dr. Eng. degree from the University of Padova in 1998 and his M.S. and Ph.D. in Electrical Engineering from the University of California at Berkeley, in 2003 and 2005 respectively. After a postdoctoral position at Stanford University, Dr. Sinopoli was member of the faculty at Carnegie Mellon University from 2007 to 2019, where he was a professor in the Department of Electrical and Computer Engineering with courtesy appointments in Mechanical Engineering and in the Robotics Institute and co-director of the Smart Infrastructure Institute. His research interests include modeling, analysis and design of Resilient Cyber-Physical Systems with applications to Smart Interdependent Infrastructures Systems, such as Energy and Transportation, Internet of Things and control of computing systems. More recently, he has been working on understanding connection between Machine and human learning and influence mechanisms in multi agent systems.