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Constrained-cost adaptive dynamic programming for optimal control of discrete-time nonlinear systems 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 卷号: 35, 期号: 3, 页码: 3251 - 3264
作者:  Wei, Qinglai;  Li, Tao
Adobe PDF(8471Kb)  |  收藏  |  浏览/下载：2/0  |  提交时间：2024/05/28
Adaptive dynamic programming  approximate dynamic programming  constrained cost  optimal control  reinforcement learning  
A Data-Driven Iterative Learning Approach for Optimizing the Train Control Strategy 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2023, 卷号: 19, 期号: 7, 页码: 7885-7893
作者:  Su, Shuai;  Zhu, Qingyang;  Liu, Junqing;  Tang, Tao;  Wei, Qinglai;  Cao, Yuan
收藏  |  浏览/下载：98/0  |  提交时间：2023/11/17
Deep reinforcement learning (RL)  driving strategy  energy-efficient train control (EETC)  soft actorcritic (SAC)  
Event-Triggered Deep Reinforcement Learning Using Parallel Control: A Case Study in Autonomous Driving 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2023, 卷号: 8, 期号: 4, 页码: 2821-2831
作者:  Lu, Jingwei;  Han, Liyuan;  Wei, Qinglai;  Wang, Xiao;  Dai, Xingyuan;  Wang, Fei-Yue
收藏  |  浏览/下载：89/0  |  提交时间：2023/11/17
Autonomous vehicles  Decision making  Path planning  Training  Optimal control  Deep learning  Complex systems  Autonomous driving  deep reinforcement learning  deep Q-network  event-triggered control  parallel control