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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:57/21  |  提交时间:2024/05/28
Adaptive dynamic programming  approximate dynamic programming  constrained cost  optimal control  reinforcement learning  
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:62/3  |  提交时间:2023/11/16
Large-scale multiagent  neighboring communication  reinforcement learning (RL)  variational information flow  
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:250/12  |  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  
Meta-Prototypical Learning for Domain-Agnostic Few-Shot Recognition 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 1-7
作者:  Wang RQ(王瑞琪);  Zhang XY(张煦尧);  Liu CL(刘成林)
Adobe PDF(1403Kb)  |  收藏  |  浏览/下载:271/54  |  提交时间:2022/01/27
domain-agnostic few-shot recognition  image classification  meta-learning  prototypical learning  
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:264/12  |  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)  
Spiking Adaptive Dynamic Programming Based on Poisson Process for Discrete-Time Nonlinear Systems 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 11
作者:  Wei, Qinglai;  Han, Liyuan;  Zhang, Tielin
Adobe PDF(2904Kb)  |  收藏  |  浏览/下载:239/16  |  提交时间:2022/01/27
Maximum likelihood estimation (MLE)  Nonlinear systems  Optimal control  Poisson process  Spike train  Spiking Adaptive dynamic programming(SADP)  
EDP: An Efficient Decomposition and Pruning Scheme for Convolutional Neural Network Compression 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 卷号: 32, 期号: 10, 页码: 4499-4513
作者:  Ruan, Xiaofeng;  Liu, Yufan;  Yuan, Chunfeng;  Li, Bing;  Hu, Weiming;  Li, Yangxi;  Maybank, Stephen
Adobe PDF(3625Kb)  |  收藏  |  浏览/下载:356/48  |  提交时间:2021/06/17
Data-driven  low-rank decomposition  model compression and acceleration  structured pruning  
Optimal Elevator Group Control via Deep Asynchronous Actor-Critic Learning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 12, 页码: 5245-5256
作者:  Wei, Qinglai;  Wang, Lingxiao;  Liu, Yu;  Polycarpou, Marios M.
Adobe PDF(4019Kb)  |  收藏  |  浏览/下载:382/86  |  提交时间:2021/03/08
Elevators  Optimal control  Backpropagation  Machine learning  Neural networks  Learning (artificial intelligence)  Actor  –critic  adaptive dynamic programming  deep learning (DL)  elevator group control (EGC)  optimal control  reinforcement learning (RL)  
Neural Encoding and Decoding With Distributed Sentence Representations 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 0, 期号: 0, 页码: 0
作者:  jingyuan sun;  shaonan wang;  jiajun zhang;  chengqing zong
浏览  |  Adobe PDF(2424Kb)  |  收藏  |  浏览/下载:232/75  |  提交时间:2020/10/13
brain-machine interface, distributed semantic representations, neural decoding, neural encoding  
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:411/126  |  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