DOLCIT Seminar

Monday March 9, 2020 4:00 PM

The Non-Stochastic Control Problem

Speaker: Elad Hazan, Computer Science, Princeton Univeristy
Location: Annenberg 105

Linear dynamical systems are a continuous subclass of reinforcement learning models that are widely used in robotics, finance, engineering, and meteorology. Classical control, since the work of Kalman, has focused on dynamics with Gaussian i.i.d. noise, quadratic loss functions and, in terms of provably efficient algorithms, known statespace realization and observed state. We'll discuss how to apply new machine learning methods which relax all of the above: efficient control with adversarial noise, general loss functions, unknown systems, and partial observation.

Series RSRG/DOLCIT Seminar Series

Contact: Sydney Garstang sydney@caltech.edu