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Multi-task safe reinforcement learning for navigating intersections in dense traffic 期刊论文
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2023, 卷号: 360, 期号: 17, 页码: 13737-13760
作者:  Liu, Yuqi;  Gao, Yinfeng;  Zhang, Qichao;  Ding, Dawei;  Zhao, Dongbin
Adobe PDF(3095Kb)  |  收藏  |  浏览/下载：61/7  |  提交时间：2024/02/22
NVIF: Neighboring Variational Information Flow for Cooperative Large-Scale Multiagent Reinforcement Learning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 页码: 13
作者:  Chai, Jiajun;  Zhu, Yuanheng;  Zhao, Dongbin
Adobe PDF(2469Kb)  |  收藏  |  浏览/下载：55/1  |  提交时间：2023/11/16
Large-scale multiagent  neighboring communication  reinforcement learning (RL)  variational information flow  
Dynamic-horizon model-based value estimation with latent imagination 期刊论文
IEEE Transactions on Neural Networks and Learning Systems, 2022, 页码: 1-14
作者:  Wang JJ(王俊杰);  Zhang QC(张启超);  Zhao DB(赵冬斌)
Adobe PDF(2305Kb)  |  收藏  |  浏览/下载：176/64  |  提交时间：2023/05/30
Latent world model  model-based value expansion (MVE)  reinforcement learning  reinforcement learning  
Online Minimax Q Network Learning for Two-Player Zero-Sum Markov Games 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 卷号: 33, 期号: 3, 页码: 1228-1241
作者:  Zhu, Yuanheng;  Zhao, Dongbin
Adobe PDF(2838Kb)  |  收藏  |  浏览/下载：228/4  |  提交时间：2022/06/10
Games  Nash equilibrium  Mathematical model  Markov processes  Convergence  Dynamic programming  Training  Deep reinforcement learning (DRL)  generalized policy iteration (GPI)  Markov game (MG)  Nash equilibrium  Q network  zero sum  
UNMAS: Multiagent Reinforcement Learning for Unshaped Cooperative Scenarios 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 12
作者:  Chai, Jiajun;  Li, Weifan;  Zhu, Yuanheng;  Zhao, Dongbin;  Ma, Zhe;  Sun, Kewu;  Ding, Jishiyu
Adobe PDF(3402Kb)  |  收藏  |  浏览/下载：269/31  |  提交时间：2022/01/27
Multi-agent systems  Training  Task analysis  Reinforcement learning  Sun  Learning systems  Semantics  Centralized training with decentralized execution (CTDE)  multiagent  reinforcement learning  StarCraft II  
Event-Triggered Communication Network With Limited-Bandwidth Constraint for Multi-Agent Reinforcement Learning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 13
作者:  Hu, Guangzheng;  Zhu, Yuanheng;  Zhao, Dongbin;  Zhao, Mengchen;  Hao, Jianye
Adobe PDF(4187Kb)  |  收藏  |  浏览/下载：237/6  |  提交时间：2022/01/27
Bandwidth  Protocols  Reinforcement learning  Task analysis  Optimization  Communication networks  Multi-agent systems  Event trigger  limited bandwidth  multi-agent communication  multi-agent reinforcement learning (MARL)  
BNAS: Efficient Neural Architecture Search Using Broad Scalable Architecture 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 期号: 0, 页码: 0
作者:  Ding ZX(丁子祥);  Yaran, Chen;  Nannan, Li;  Dingbin, Zhao;  Zhiquan, Sun;  C. L. Philip Chen
Adobe PDF(2713Kb)  |  收藏  |  浏览/下载：190/44  |  提交时间：2022/01/06
Broad convolutional neural network (BCNN), image classification, neural architecture search (NAS), reinforcement learning (RL)  
Optimal Feedback Control of Pedestrian Flow in Heterogeneous Corridors 期刊论文
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2021, 卷号: 18, 期号: 3, 页码: 1097-1108
作者:  Zhu, Yuanheng;  Zhao, Dongbin;  He, Haibo
Adobe PDF(2666Kb)  |  收藏  |  浏览/下载：211/9  |  提交时间：2021/08/15
Microscopy  Feedback control  Mathematical model  Data models  Dynamic programming  Psychology  Computational modeling  Adaptive dynamic programming (ADP)  heterogeneous corridors  macroscopic pedestrian dynamics  optimal feedback control  pedestrian flow  
Invariant Adaptive Dynamic Programming for Discrete-Time Optimal Control 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2020, 卷号: 50, 期号: 11, 页码: 3959-3971
作者:  Zhu, Yuanheng;  Zhao, Dongbin;  He, Haibo
Adobe PDF(2079Kb)  |  收藏  |  浏览/下载：191/9  |  提交时间：2021/01/07
Optimal control  Discrete-time systems  Heuristic algorithms  Dynamic programming  Convergence  Artificial intelligence  Nonlinear systems  Adaptive dynamic programming  discrete-time systems  invariant admissibility  optimal control  policy iteration  sum of squares  
Deep Reinforcement Learning-Based Automatic Exploration for Navigation in Unknown Environment 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 6, 页码: 2064-2076
作者:  Li, Haoran;  Zhang, Qichao;  Zhao, Dongbin
浏览  |  Adobe PDF(4274Kb)  |  收藏  |  浏览/下载：394/121  |  提交时间：2020/08/03
Robot sensing systems  Navigation  Entropy  Neural networks  Task analysis  Planning  Automatic exploration  deep reinforcement learning (DRL)  optimal decision  partial observation