Abstract: This article proposes a data-driven model-free inverse Q-learning algorithm for continuous-time linear quadratic regulators (LQRs). Using an agent’s trajectories of states and optimal ...

This project aims to develop a computational framework combining computer vision, computer graphics, and machine learning to accelerate and improve the design and simulation of camera lenses.

Abstract: With autonomous robots becoming increasingly integrated into human society, the efficiency of their path optimization is of paramount importance. To address the issue of redundant states in ...