Search Results for author: Jingliang Duan

Found 17 papers, 3 papers with code

Primal-dual Estimator Learning: an Offline Constrained Moving Horizon Estimation Method with Feasibility and Near-optimality Guarantees

no code implementations6 Apr 2022 Wenhan Cao, Jingliang Duan, Shengbo Eben Li, Chen Chen, Chang Liu, Yu Wang

Both the primal and dual estimators are learned from data using supervised learning techniques, and the explicit sample size is provided, which enables us to guarantee the quality of each learned estimator in terms of feasibility and optimality.

Self-learned Intelligence for Integrated Decision and Control of Automated Vehicles at Signalized Intersections

no code implementations24 Oct 2021 Yangang Ren, Jianhua Jiang, Dongjie Yu, Shengbo Eben Li, Jingliang Duan, Chen Chen, Keqiang Li

This paper develops the dynamic permutation state representation in the framework of integrated decision and control (IDC) to handle signalized intersections with mixed traffic flows.

Autonomous Driving Decision Making

Integrated Decision and Control: Towards Interpretable and Computationally Efficient Driving Intelligence

2 code implementations18 Mar 2021 Yang Guan, Yangang Ren, Qi Sun, Shengbo Eben Li, Haitong Ma, Jingliang Duan, Yifan Dai, Bo Cheng

In this paper, we present an interpretable and computationally efficient framework called integrated decision and control (IDC) for automated vehicles, which decomposes the driving task into static path planning and dynamic optimal tracking that are structured hierarchically.

Autonomous Driving Model-based Reinforcement Learning +1

Approximate Optimal Filter for Linear Gaussian Time-invariant Systems

no code implementations9 Mar 2021 Kaiming Tang, Shengbo Eben Li, Yuming Yin, Yang Guan, Jingliang Duan, Wenhan Cao, Jie Li

The equivalence holds given certain conditions about initial state distributions and policy formats, in which the system state is the estimation error, control input is the filter gain, and control objective function is the accumulated estimation error.

Decision-Making under On-Ramp merge Scenarios by Distributional Soft Actor-Critic Algorithm

no code implementations8 Mar 2021 Yiting Kong, Yang Guan, Jingliang Duan, Shengbo Eben Li, Qi Sun, Bingbing Nie

In this paper, we propose an RL-based end-to-end decision-making method under a framework of offline training and online correction, called the Shielded Distributional Soft Actor-critic (SDSAC).

Decision Making

Mixed Policy Gradient

2 code implementations23 Feb 2021 Yang Guan, Jingliang Duan, Shengbo Eben Li, Jie Li, Jianyu Chen, Bo Cheng

MPG contains two types of PG: 1) data-driven PG, which is obtained by directly calculating the derivative of the learned Q-value function with respect to actions, and 2) model-driven PG, which is calculated using BPTT based on the model-predictive return.

Decision Making

Recurrent Model Predictive Control

no code implementations23 Feb 2021 Zhengyu Liu, Jingliang Duan, Wenxuan Wang, Shengbo Eben Li, Yuming Yin, Ziyu Lin, Qi Sun, Bo Cheng

This paper proposes an off-line algorithm, called Recurrent Model Predictive Control (RMPC), to solve general nonlinear finite-horizon optimal control problems.

Recurrent Model Predictive Control: Learning an Explicit Recurrent Controller for Nonlinear Systems

no code implementations20 Feb 2021 Zhengyu Liu, Jingliang Duan, Wenxuan Wang, Shengbo Eben Li, Yuming Yin, Ziyu Lin, Bo Cheng

This paper proposes an offline control algorithm, called Recurrent Model Predictive Control (RMPC), to solve large-scale nonlinear finite-horizon optimal control problems.

Separated Proportional-Integral Lagrangian for Chance Constrained Reinforcement Learning

no code implementations17 Feb 2021 Baiyu Peng, Yao Mu, Jingliang Duan, Yang Guan, Shengbo Eben Li, Jianyu Chen

Taking a control perspective, we first interpret the penalty method and the Lagrangian method as proportional feedback and integral feedback control, respectively.

Autonomous Driving reinforcement-learning

Ternary Policy Iteration Algorithm for Nonlinear Robust Control

no code implementations14 Jul 2020 Jie Li, Shengbo Eben Li, Yang Guan, Jingliang Duan, Wenyu Li, Yuming Yin

The simulation results show that the TPI algorithm can converge to the optimal solution for the linear plant, and has high resistance to disturbances for the nonlinear plant.

Improving Generalization of Reinforcement Learning with Minimax Distributional Soft Actor-Critic

no code implementations13 Feb 2020 Yangang Ren, Jingliang Duan, Shengbo Eben Li, Yang Guan, Qi Sun

In this paper, we introduce the minimax formulation and distributional framework to improve the generalization ability of RL algorithms and develop the Minimax Distributional Soft Actor-Critic (Minimax DSAC) algorithm.

Autonomous Driving Decision Making +1

Distributional Soft Actor-Critic: Off-Policy Reinforcement Learning for Addressing Value Estimation Errors

2 code implementations9 Jan 2020 Jingliang Duan, Yang Guan, Shengbo Eben Li, Yangang Ren, Bo Cheng

In reinforcement learning (RL), function approximation errors are known to easily lead to the Q-value overestimations, thus greatly reducing policy performance.

Continuous Control reinforcement-learning

Direct and indirect reinforcement learning

no code implementations23 Dec 2019 Yang Guan, Shengbo Eben Li, Jingliang Duan, Jie Li, Yangang Ren, Qi Sun, Bo Cheng

Reinforcement learning (RL) algorithms have been successfully applied to a range of challenging sequential decision making and control tasks.

Decision Making reinforcement-learning

Adaptive dynamic programming for nonaffine nonlinear optimal control problem with state constraints

no code implementations26 Nov 2019 Jingliang Duan, Zhengyu Liu, Shengbo Eben Li, Qi Sun, Zhenzhong Jia, Bo Cheng

CADP linearizes the constrained optimization problem locally into a quadratically constrained linear programming problem, and then obtains the optimal update of the policy network by solving its dual problem.

Generalized Policy Iteration for Optimal Control in Continuous Time

no code implementations11 Sep 2019 Jingliang Duan, Shengbo Eben Li, Zhengyu Liu, Monimoy Bujarbaruah, Bo Cheng

This paper proposes the Deep Generalized Policy Iteration (DGPI) algorithm to find the infinite horizon optimal control policy for general nonlinear continuous-time systems with known dynamics.

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