Abstract:
Stability and analysis of multiagent network systems with state-dependent switching typologies have been a fundamental and longstanding challenge in control, social sciences, and many other related fields. These already complex systems become further complicated once one accounts for asymmetry or heterogeneity of the underlying agents/dynamics. Despite extensive progress in the analysis of conventional networked decision systems where the network evolution and state dynamics are driven by independent or weakly coupled processes, most of the existing results fail to address multiagent systems where the network and state dynamics are highly coupled and evolve based on the status of heterogeneous agents. Motivated by numerous applications of such dynamics in social sciences, in this talk, we provide a new direction toward the analysis of dynamic networks of heterogeneous agents under time-varying environments. In particular, we show that the evolution of the coupled state-network multiagent dynamics can often be viewed as iterates of a primal-dual algorithm for a static constrained optimization/saddle-point problem. This view bridges the Lyapunov stability of state-dependent network dynamics and frequently used optimization techniques such as block coordinated descent, mirror descent, the Newton method, and the subgradient method. As a result, we show Lyapunov stability and convergence of several challenging problems from opinion dynamics using a simple application of our framework. Finally, we support our theoretical results through numerical simulations from social science.
Bio: Rasoul Etesami is an Assistant Professor in the Department of Industrial and Systems Engineering (ISE) at the University of Illinois at Urbana-Champaign. He is also affiliated with the Coordinated Science Laboratory (CSL), where he is a member of the Decision and Control (DCL) group. From 2016 to 2017, he was a Postdoctoral Research Fellow in the Department of Electrical Engineering at Princeton University and WINLAB and spent the summer of 2015 as a Research Intern at Alcatel-Lucent Bell Labs. He received his Ph.D. degree in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign, where he was the first recipient of the Best CSL Ph.D. Thesis Award in 2016. His research involves understanding complex social, communication, and decision-making systems using tools from control theory, game theory, and optimization theory. His research is supported by the National Science Foundation CAREER Award, and he is currently serving as an Associate Editor of the Journal of IET Smart Grid.
