In many decentralized control systems, in particular, those arising in smart grids and communication networks, the dynamics of an agent are influenced by the state of the others only only through the mean-field of the population. We investigate team optimal control of such systems. By exploiting the exchageability of the agents, we identify an information state and use it to obtain a dynamic programming decomposition of the system. Our solution provides team optimal solution for systems with arbitrary number of agents. The complexity of the solution increases exponentially with the number of agents that allows us solve systems with moderate (100s to 1000s) number of agents.
Joint work with Jalal Arabneydi
Speaker Bio: Aditya Mahajan is Assistant Professor of Electrical and Computer Engineering at McGill University, Montreal, QC, Canada. He is a member of the McGill Center of Intelligent Machines (CIM) and Groupe d’tudes et de recherche en analyse des dcisions (GERAD). From 2008 to 2010, he was a Postdoctoral Researcher in the Department of Electrical Engineering, Yale University, New Haven, CT, USA. His principal research interests include decentralized stochastic control, team theory, multi-armed bandits, real-time communication, information theory, and discrete event systems.