Location
MC 5501
Speaker
Peter E. Caines | McGill University
Title
Mean Field Control and Games on Large Networks
Abstract
Contemporary technological systems often have a network structure of both great scale and complexity, while the natural world reveals a vast array of complex networks which includes the human microbiome and the brain. All these networks support dynamical processes, often with feedback loops which are inherent, designed or a combination of both.
In this talk, results on stochastic control and mean field games for large populations on large networks will be presented using notions of network limits. In particular, a new decomposition, or classification, of all network limits will be employed which, necessarily, covers both dense and sparse networks. The principal results include the existence and uniqueness of optima and Nash equilibria together with their approximation to source problems with finite populations on finite networks.
Speaker Bio
Peter E. Caines received the BA in mathematics from Oxford University in 1967 and the PhD in systems and control theory in 1970 from Imperial College, University of London, supervised by David Q. Mayne, FRS. Following PDF and visiting positions he joined McGill University in 1980, where he is Distinguished James McGill Professor and Macdonald Chair in the Department of Electrical and Computer Engineering. He received the IEEE Control Systems Society Bode Lecture Prize (2009), is a Fellow of IFAC, CIFAR, SIAM, IEEE, the IMA (UK) and the Royal Society of Canada (2003), and is a member of Professional Engineers Ontario. His monograph, Linear Stochastic Systems (Wiley, 1988), is now a SIAM Classic and his research interests include stochastic and hybrid systems, and mean field control and games on complex networks.