593 citations · 1.8k across the 57 of their papers we have counts for
7 papers · 1 filter
Learn Zero-Constraint-Violation Policy in Model-Free Constrained Reinforcement Learning
Haitong Ma, Changliu Liu, Shengbo Eben Li +3
In the trial-and-error mechanism of reinforcement learning (RL), a notorious contradiction arises when we expect to learn a safe policy: how to learn a safe policy without enough d…
Self-learned Intelligence for Integrated Decision and Control of Automated Vehicles at Signalized Intersections
Yangang Ren, Jianhua Jiang, Dongjie Yu +4
Intersection is one of the most complex and accident-prone urban scenarios for autonomous driving wherein making safe and computationally efficient decisions is non-trivial. Curren…
Joint Synthesis of Safety Certificate and Safe Control Policy using Constrained Reinforcement Learning
Haitong Ma, Changliu Liu, Shengbo Eben Li +2
Safety is the major consideration in controlling complex dynamical systems using reinforcement learning (RL), where the safety certificate can provide provable safety guarantee. A…
Optimization Landscape of Gradient Descent for Discrete-time Static Output Feedback
Jingliang Duan, Jie Li, Shengbo Eben Li +1
In this paper, we analyze the optimization landscape of gradient descent methods for static output feedback (SOF) control of discrete-time linear time-invariant systems with quadra…
Fixed-Dimensional and Permutation Invariant State Representation of Autonomous Driving
Jingliang Duan, Dongjie Yu, Shengbo Eben Li +4
In this paper, we propose a new state representation method, called encoding sum and concatenation (ESC), for the state representation of decision-making in autonomous driving. Unl…
Mixed Policy Gradient: off-policy reinforcement learning driven jointly by data and model
Yang Guan, Jingliang Duan, Shengbo Eben Li +3
Reinforcement learning (RL) shows great potential in sequential decision-making. At present, mainstream RL algorithms are data-driven, which usually yield better asymptotic perform…
Recurrent Model Predictive Control: Learning an Explicit Recurrent Controller for Nonlinear Systems
Zhengyu Liu, Jingliang Duan, Wenxuan Wang +4
This paper proposes an offline control algorithm, called Recurrent Model Predictive Control (RMPC), to solve large-scale nonlinear finite-horizon optimal control problems. It can b…