DEPARTMENT OF MATHEMATICAL SCIENCES

APPLIED AND COMPUTATIONAL MATHEMATICS SEMINAR

**Speaker:** Sui Tang, JHU

**Title: ***
Learning interaction laws in high dimensional agent-based dynamics from observations
*

**Abstract:**
In different disciplines, inferring the laws of interaction of agents in complex dynamical systems from observational data is a fundamental challenge. We propose a non-parametric statistical learning approach to estimate the governing laws of distance-based interactions, with no reference or assumption about their analytical form, from data consisting trajectories of interacting agents. We demonstrate the effectiveness of our learning approach both by providing theoretical guarantees, and numerical tests on several prototypical systems.

**Time:** Friday, November 9, 2018, 1:30-2:30pm

**Place:** Exploratory Hall, Room 4106

Department of Mathematical Sciences

George Mason University

4400 University Drive, MS 3F2

Fairfax, VA 22030-4444

http://math.gmu.edu/

Tel. 703-993-1460, Fax. 703-993-1491