This talk will discuss the placement and control of sensors to maximize a global objective, such as estimation quality or detection performance. First, we consider a distributed maximization problem in which a group of agents must each choose a strategy from their strategy set. The global objective is to maximize a submodular function of the strategies chosen by each agent. However, each agent has access to only a limited number of other agents' choices. This talk will characterize how the limited information affects the performance when agents make choices in a greedy manner.
Second, we discuss a related problem in scheduling a group of sensors to estimate the state of an uncertain linear dynamic system. The goal is to choose a subset of sensors at each time step so as to minimize the covariance of the state estimation error. We show that while the resulting objective function is not, in general, submodular, a modification of a greedy algorithm can be made to obtain performance guarantees. Third and finally, we discuss the problem of routing sensors to detect adversarial events. We show how randomized routing algorithms can be used both to improve detection performance, and to reduce the ability of an adversary to predict future sensor routes.
Bio: Stephen L. Smith is an associate professor in Electrical and Computer Engineering at the University of Waterloo. He received the BSc degree from Queen’s University in 2003, the MASc degree from the University of Toronto in 2005, and the PhD degree from the University of California, Santa Barbara in 2009. From 2009 to 2011 he was a postdoctoral researcher with the Computer Science & Artificial Intelligence Lab at the Massachusetts Institute of Technology. Dr. Smith is a recipient of the 2016 Early Researcher Award from the Ontario Ministry of Research and Innovation, the NSERC Discovery Accelerator Supplement Award, and an Outstanding Performance Award from the University of Waterloo. His main research interests lie in control and optimization for autonomous systems, with a particular emphasis on robotic motion planning and coordination.
Bienvenue à tous!