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| Boosting On-Policy Actor–Critic With Shallow Updates in Critic 期刊论文 IEEE Transactions on Neural Networks and Learning Systems, 2024, 页码: 1-10 作者: Luntong Li; Yuanheng Zhu![](/image/person.jpg)
Adobe PDF(9953Kb)  |   收藏  |  浏览/下载:58/19  |  提交时间:2024/06/05 |
| Multiexperience-Assisted Efficient Multiagent Reinforcement Learning 期刊论文 IEEE Transactions on Neural Networks and Learning Systems, 2023, 页码: 1-15 作者: Zhang TL(张天乐) ; Liu Z(刘振) ; Yi JQ(易建强) ; Wu SG(吴士广) ; Pu ZQ(蒲志强) ; Zhao YJ(赵彦杰)
Adobe PDF(2718Kb)  |   收藏  |  浏览/下载:325/108  |  提交时间:2023/06/02 |
| 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)![](/image/person.jpg)
Adobe PDF(2305Kb)  |   收藏  |  浏览/下载:200/70  |  提交时间:2023/05/30 Latent world model model-based value expansion (MVE) reinforcement learning reinforcement learning |
| Integrating Relational Knowledge With Text Sequences for Script Event Prediction 期刊论文 IEEE Transactions on Neural Networks and Learning Systems, 2023, 页码: early access 作者: Zikang Wang ; Linjing Li ; Daniel Zeng![](/image/person.jpg)
Adobe PDF(3215Kb)  |   收藏  |  浏览/下载:406/106  |  提交时间:2023/03/20 |
| Attention enhanced reinforcement learning for multi-agent cooperation 期刊论文 IEEE Transactions on Neural Networks and Learning Systems, 2022, 期号: 2022, 页码: 1-15 作者: Zhiqiang Pu ; Huimu Wang ; Zhen Liu ; Jianqiang Yi ; Shiguang Wu![](/image/person.jpg)
Adobe PDF(2967Kb)  |   收藏  |  浏览/下载:259/52  |  提交时间:2022/04/02 Attention mechanism deep reinforcement learning (DRL) graph convolutional networks multi agent systems |
| 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![](/image/person.jpg)
Adobe PDF(5344Kb)  |   收藏  |  浏览/下载:271/89  |  提交时间:2022/04/02 Collision avoidance deep reinforcement learning (DRL) formation control leader–follower |