no code implementations • 12 Jul 2022 • Victor D. Dorobantu, Kamyar Azizzadenesheli, Yisong Yue
We study policy optimization problems for deterministic Markov decision processes (MDPs) with metric state and action spaces, which we refer to as Metric Policy Optimization Problems (MPOPs).
no code implementations • 22 Mar 2022 • Andrew J. Taylor, Victor D. Dorobantu, Ryan K. Cosner, Yisong Yue, Aaron D. Ames
Existing design paradigms do not address the gap between theory (controller design with continuous time models) and practice (the discrete time sampled implementation of the resulting controllers); this can lead to poor performance and violations of safety for hardware instantiations.
no code implementations • 21 Nov 2020 • Andrew J. Taylor, Victor D. Dorobantu, Sarah Dean, Benjamin Recht, Yisong Yue, Aaron D. Ames
Modern nonlinear control theory seeks to endow systems with properties such as stability and safety, and has been deployed successfully across various domains.
no code implementations • 18 Mar 2019 • Andrew J. Taylor, Victor D. Dorobantu, Meera Krishnamoorthy, Hoang M. Le, Yisong Yue, Aaron D. Ames
The goal of this paper is to understand the impact of learning on control synthesis from a Lyapunov function perspective.
no code implementations • 4 Mar 2019 • Andrew J. Taylor, Victor D. Dorobantu, Hoang M. Le, Yisong Yue, Aaron D. Ames
Many modern nonlinear control methods aim to endow systems with guaranteed properties, such as stability or safety, and have been successfully applied to the domain of robotics.