Citation:
N. Agarwal, B. Bullins, E. Hazan, S. M. Kakade, and K. Singh, Online Control with Adversarial Disturbances. ICML: ArXiv Report, 2019.
Abstract:
We study the control of a linear dynamical system with adversarial disturbances (as opposed to statistical noise). The objective we consider is one of regret: we desire an online control procedure that can do nearly as well as that of a procedure that has full knowledge of the disturbances in hindsight. Our main result is an efficient algorithm that provides nearly tight regret bounds for this problem. From a technical standpoint, this work generalizes upon previous work in two main aspects: our model allows for adversarial noise in the dynamics, and allows for general convex costs.See also: 2019