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Adaptive model-based dynamic event-triggered output feedback control of a robotic manipulator with disturbance 期刊论文
ISATransactions, 2021, 页码: 64-78
作者:  Gao jie;  Kang Erlong;  He Wei;  Qiao hong
Adobe PDF(2719Kb)  |  收藏  |  浏览/下载:251/92  |  提交时间:2022/06/14
SOZIL: Self-Optimal Zero-shot Imitation Learning 期刊论文
IEEE Trans on Cognitive and Developmental System, 2021, 期号: 1, 页码: 1
作者:  Peng Hao;  Tao Lu;  Shaowei Cui;  Junhang Wei;  Yinghao Cai;  Shuo Wang
Adobe PDF(13840Kb)  |  收藏  |  浏览/下载:152/23  |  提交时间:2022/04/08
imitation learning  learning from observation  keyframe demonstration  
Aspiration dynamics generate robust predictions in heterogeneous populations 期刊论文
Nature Communications, 2021, 期号: 12, 页码: 3250
作者:  Zhou L(周雷);  Wu B;  Du J;  Wang L
Adobe PDF(939Kb)  |  收藏  |  浏览/下载:146/47  |  提交时间:2022/04/06
Complex networks, game, aspiration, evolutionary dynamics  
Formation control with collision avoidance through deep reinforcement learning using model-guided demonstration 期刊论文
IEEE Transactions on Neural Networks and Learning Systems, 2021, 卷号: 32, 期号: 6, 页码: 2358-2372
作者:  Zezhi Sui;  Zhiqiang Pu;  Jianqiang Yi;  Shiguang Wu
Adobe PDF(5344Kb)  |  收藏  |  浏览/下载:227/75  |  提交时间:2022/04/02
Collision avoidance  deep reinforcement learning (DRL)  formation control  leader–follower  
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:241/25  |  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
收藏  |  浏览/下载:208/0  |  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 Novel Parallel Control Method for Continuous-Time Linear Output Regulation With Disturbances 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2021, 页码: 11
作者:  Wei, Qinglai;  Li, Hongyang;  Wang, Fei-Yue
Adobe PDF(1665Kb)  |  收藏  |  浏览/下载:243/39  |  提交时间:2022/01/27
Regulators  Regulation  Control systems  Stability analysis  Asymptotic stability  Eigenvalues and eigenfunctions  Control theory  Continuous-time linear systems  output regulation  parallel control theory  parallel regulators  parallel systems  
Data Augmented Deep Behavioral Cloning for Urban Traffic Control Operations Under a Parallel Learning Framework 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2021, 卷号: 23, 期号: 6, 页码: 5128-5137
作者:  Li, Xiaoshuang;  Ye, Peijun;  Jin, Junchen;  Zhu, Fenghua;  Wang, Fei-Yue
Adobe PDF(2319Kb)  |  收藏  |  浏览/下载:297/58  |  提交时间:2022/01/27
Generative adversarial networks  Data models  Gallium nitride  Task analysis  Complex systems  Intelligent traffic signal operations  deep behavioral cloning  
A Unified Shared-Private Network with Denoising for Dialogue State Tracking 期刊论文
JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY, 2021, 卷号: 36, 期号: 6, 页码: 1407-1419
作者:  Liu QB(刘庆斌);  He SZ(何世柱);  Liu K(刘康);  Liu SP(刘升平);  Zhao J(赵军)
Adobe PDF(997Kb)  |  收藏  |  浏览/下载:219/68  |  提交时间:2022/01/19
dialogue state tracking  unified strategy  shared-private network  reinforcement learning  
Robust Cross-lingual Task-oriented Dialogue 期刊论文
ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING, 2021, 卷号: 20, 期号: 6, 页码: 24
作者:  Xiang, Lu;  Zhu, Junnan;  Zhao, Yang;  Zhou, Yu;  Zong, Chengqing
Adobe PDF(1935Kb)  |  收藏  |  浏览/下载:268/58  |  提交时间:2021/12/28
Cross-lingual  dialogue system  adversarial learning  knowledge  robustness