Academy of Mathematics and Systems Science, CAS
Colloquia & Seminars

Speaker:	Dr. Fei Lu, Johns Hopkins University
Inviter:	洪佳林研究员
Title:	Nonparametric inference of interaction laws in particles/agent systems
Time & Venue:	2019.7.11 16:00-17:00 Z311
Abstract:	Self-interacting systems of particles/agents arise in many areas of science, such as particle systems in physics, flocking and swarming models in biology, and opinion dynamics in social science. An interesting question is to learn the laws of interaction between the particles/agents from data consisting of trajectories. In the case of distance-based interaction laws, we present efficient regression algorithms to estimate the interaction kernels, and we develop a nonparametric statistical learning theory addressing identifiability, consistency and optimal rate of convergence of the estimators. In particular, we use the theory to guide the design of the regression algorithms as well as statistical methods for model selection. An open question about a coercivity condition for identifiability and an ongoing work related to data-based eigenfunction problem will be discussed. (Joint work with Mauro Maggioni, Sui Tang and Ming Zhong).