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Titlebook: Knowledge Science, Engineering and Management; 13th International C Gang Li,Heng Tao Shen,Xiang Zhao Conference proceedings 2020 Springer N

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41#
發(fā)表于 2025-3-28 17:17:48 | 只看該作者
Wencong Wang,Lan Huang,Hao Liu,Jia Zeng,Shiqi Sun,Kainuo Li,Kangping Wang
42#
發(fā)表于 2025-3-28 22:16:26 | 只看該作者
Gong Xudong,Jia Hongda,Zhou Xing,Feng Dawei,Ding Bo,Xu Jie
43#
發(fā)表于 2025-3-29 01:17:13 | 只看該作者
Shaokang Zhang,Huailiang Peng,Yanan Cao,Lei Jiang,Qiong Dai,Jianlong Tan
44#
發(fā)表于 2025-3-29 03:55:13 | 只看該作者
Cheng He,Chao Peng,Na Li,Xiang Chen,Zhengfeng Yang,Zhenhao Hu
45#
發(fā)表于 2025-3-29 07:36:37 | 只看該作者
46#
發(fā)表于 2025-3-29 14:04:14 | 只看該作者
47#
發(fā)表于 2025-3-29 18:35:18 | 只看該作者
0302-9743 zed in the following topical sections: machine learning; recommendation algorithms and systems; social knowledge analysis and management; text mining and document analysis; and deep learning..*The conference was held virtually due to the COVID-19 pandemic..978-3-030-55392-0978-3-030-55393-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
48#
發(fā)表于 2025-3-29 23:09:53 | 只看該作者
MA-TREX: Mutli-agent Trajectory-Ranked Reward Extrapolation via Inverse Reinforcement Learnings adopted in the iteration process, by which the self-generated data required subsequently is only one third of the initial demonstrations. Experimental results on several multi-agent collaborative tasks demonstrate that the MA-TREX can effectively surpass the demonstrators and obtain the same level reward as the ground truth quickly and stably.
49#
發(fā)表于 2025-3-30 00:38:47 | 只看該作者
An Incremental Learning Network Model Based on Random Sample Distribution Fittingial samples were mixed with new real data as training data. The experiments with proper parameters show that new features from new real data can be learned as well as the old features are not forgot catastrophically.
50#
發(fā)表于 2025-3-30 06:10:06 | 只看該作者
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