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Data Generation Feedback Relearning Control for Unmodeled Nonlinear Systems 期刊论文
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE, 2023, 页码: 12
作者:  Zhang, Yong;  Mu, Chaoxu;  Zhao, Dongbin
收藏  |  浏览/下载:59/0  |  提交时间:2023/11/16
Data models  Real-time systems  Heuristic algorithms  Mathematical models  Adaptation models  Approximation algorithms  Cost function  Data generation model  feedback relearning control  delayed neural network  reinforcement learning  unmodeled nonlinear system  
A Hierarchical Deep Reinforcement Learning Framework for 6-DOF UCAV Air-to-Air Combat 期刊论文
IEEE Transactions on Systems, Man and Cybernetics: Systems, 2023, 页码: DOI: 10.1109/TSMC.2023.3270444
作者:  Jiajun Chai;  Wenzhang Chen;  Yuanheng Zhu;  Zong-xin Yao,;  Dongbin Zhao
Adobe PDF(9249Kb)  |  收藏  |  浏览/下载:193/105  |  提交时间:2023/04/26
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:130/53  |  提交时间:2023/05/30
Latent world model  model-based value expansion (MVE)  reinforcement learning  reinforcement learning  
BNAS-v2: Memory-efficient and Performance-collapse-prevented Broad Neural Architecture Search 期刊论文
IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS: SYSTEMS, 2022, 卷号: 0, 期号: 0, 页码: 0
作者:  Zixiang, Ding;  Yaran, Chen;  Nannan, Li;  Dongbin, Zhao
Adobe PDF(7657Kb)  |  收藏  |  浏览/下载:174/43  |  提交时间:2022/01/07
Broad neural architecture search (BNAS), continuous relaxation, confident learning rate, partial channel connections, image classification.  
Empirical Policy Optimization for n-Player Markov Games 期刊论文
IEEE Transactions on Cybernetics, 2022, 页码: doi={10.1109/TCYB.2022.3179775}
作者:  Yuanheng Zhu;  Weifan Li;  Mengchen Zhao;  Jianye Hao;  Dongbin Zhao
Adobe PDF(1739Kb)  |  收藏  |  浏览/下载:87/35  |  提交时间:2023/04/26
Stacked BNAS: Rethinking Broad Convolutional Neural Network for Neural Architecture Search 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 卷号: 0, 期号: 0, 页码: 0
作者:  Zixiang, Ding;  Yaran, Chen;  Nannan, Li;  Dongbin, Zhao;  C.L.Philip Chen,
Adobe PDF(764Kb)  |  收藏  |  浏览/下载:180/28  |  提交时间:2022/01/07
broad neural architecture search, stacked broad convolutional neural network, knowledge embedding search, image classification.  
Missile guidance with assisted deep reinforcement learning for head-on interception of maneuvering target 期刊论文
COMPLEX & INTELLIGENT SYSTEMS, 2021, 页码: 12
作者:  Li, Weifan;  Zhu, Yuanheng;  Zhao, Dongbin
Adobe PDF(1431Kb)  |  收藏  |  浏览/下载:255/47  |  提交时间:2021/12/28
Reinforcement learning  Missile guidance  Auxiliary learning  Self-imitation learning  
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:215/23  |  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  
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
收藏  |  浏览/下载:156/0  |  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  
MGRL: Graph neural network based inference in a Markov network with Reinforcement Learning for visual navigation 期刊论文
Neurocomputing, 2021, 卷号: 0, 期号: 0, 页码: 0
作者:  Lu, Yi;  Chen, Yaran;  Zhao, Dongbin;  Li, Dong
浏览  |  Adobe PDF(976Kb)  |  收藏  |  浏览/下载:225/67  |  提交时间:2020/10/19
Visual navigation, graph neural network, Markov network, reinforcement learning, probabilistic graph model