Robust Reinforcement Learning for Risk-Sensitive Linear Quadratic Gaussian Control

no code implementations • 5 Dec 2022 • Leilei Cui, Tamer Başar, Zhong-Ping Jiang

This paper proposes a novel robust reinforcement learning framework for discrete-time linear systems with model mismatch that may arise from the sim-to-real gap.

reinforcement-learning Reinforcement Learning (RL)

Learning-Based Adaptive Optimal Control of Linear Time-Delay Systems: A Policy Iteration Approach

no code implementations • 1 Oct 2022 • Leilei Cui, Bo Pang, Zhong-Ping Jiang

This paper studies the adaptive optimal control problem for a class of linear time-delay systems described by delay differential equations (DDEs).

Autonomous Driving Reinforcement Learning (RL)

Robust Policy Optimization in Continuous-time Mixed $\mathcal{H}_2/\mathcal{H}_\infty$ Stochastic Control

no code implementations • 9 Sep 2022 • Leilei Cui, Lekan Molu

The need for known dynamics operators is circumvented and we arrive at a reinforced PO algorithm (via policy iteration) where an upper bound on the $\mathcal{H}_2$ norm is minimized (to guarantee stability) and a robustness metric is enforced by maximizing the cost with respect to a controller that includes the level of noise attenuation specified by the system's $H_\infty$ norm.

reinforcement-learning Reinforcement Learning (RL)