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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
收藏  |  浏览/下载：41/0  |  提交时间：2023/11/16
Large-scale multiagent  neighboring communication  reinforcement learning (RL)  variational information flow  
A Self-Attention-Based Deep Reinforcement Learning Approach for AGV Dispatching Systems 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 页码: 12
作者:  Wei, Qinglai;  Yan, Yutian;  Zhang, Jie;  Xiao, Jun;  Wang, Cong
收藏  |  浏览/下载：197/0  |  提交时间：2023/01/09
Automated guided vehicle (AGV) dispatching  deep learning  reinforcement learning (RL)  self-attention  
Dynamic Event-Sampled Control of Interconnected Nonlinear Systems Using Reinforcement Learning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 页码: 15
作者:  Yang, Xiong;  Xu, Mengmeng;  Wei, Qinglai
收藏  |  浏览/下载：217/0  |  提交时间：2022/07/25
Asymptotic stability  Interconnected systems  Decentralized control  Closed loop systems  Artificial neural networks  Optimal control  Nonlinear dynamical systems  Adaptive dynamic programming (ADP)  decentralized control  event-based control  interconnected system  reinforcement learning (RL)  
VGN: Value Decomposition With Graph Attention Networks for Multiagent Reinforcement Learning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 页码: 14
作者:  Wei, Qinglai;  Li, Yugu;  Zhang, Jie;  Wang, Fei-Yue
收藏  |  浏览/下载：207/0  |  提交时间：2022/07/25
Mathematical models  Task analysis  Games  Q-learning  Neural networks  Behavioral sciences  Training  Deep learning  graph attention networks (GATs)  multiagent systems  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
收藏  |  浏览/下载：194/0  |  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  
Attention Enhanced Reinforcement Learning for Multi agent Cooperation 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 页码: 15
作者:  Pu, Zhiqiang;  Wang, Huimu;  Liu, Zhen;  Yi, Jianqiang;  Wu, Shiguang
Adobe PDF(2967Kb)  |  收藏  |  浏览/下载：292/41  |  提交时间：2022/06/06
Training  Reinforcement learning  Games  Scalability  Task analysis  Standards  Optimization  Attention mechanism  deep reinforcement learning (DRL)  graph convolutional networks  multi agent systems  
Boost 3-D Object Detection via Point Clouds Segmentation and Fused 3-D GIoU-L-1 Loss 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 卷号: 33, 期号: 2, 页码: 762-773
作者:  Chen, Yaran;  Li, Haoran;  Gao, Ruiyuan;  Zhao, Dongbin
Adobe PDF(2082Kb)  |  收藏  |  浏览/下载：222/43  |  提交时间：2022/03/17
3-D object detection  generalized Intersection of Union (GIoU) loss  segmentation  
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：187/28  |  提交时间：2022/01/07
broad neural architecture search, stacked broad convolutional neural network, knowledge embedding search, image classification.  
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
收藏  |  浏览/下载：190/0  |  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)  
A Brain-Inspired Approach for Collision-Free Movement Planning in the Small Operational Space 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 12
作者:  Xing, Dengpeng;  Li, Jiale;  Zhang, Tielin;  Xu, Bo
收藏  |  浏览/下载：192/0  |  提交时间：2022/01/27
Visualization  Cameras  Planning  Task analysis  Neurons  Collision avoidance  Biology  Brain-inspired structure  collision-free movement planning  small operational space  spiking neural networks (SNNs)