Zobrazeno 1 - 10
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pro vyhledávání: '"Hong, Weijun"'
Autor:
Liu, Enhong, Suarez, Joseph, You, Chenhui, Wu, Bo, Chen, Bingcheng, Hu, Jun, Chen, Jiaxin, Zhu, Xiaolong, Zhu, Clare, Togelius, Julian, Mohanty, Sharada, Hong, Weijun, Du, Rui, Zhang, Yibing, Wang, Qinwen, Li, Xinhang, Yuan, Zheng, Li, Xiang, Huang, Yuejia, Zhang, Kun, Yang, Hanhui, Tang, Shiqi, Isola, Phillip
In this paper, we present the results of the NeurIPS-2022 Neural MMO Challenge, which attracted 500 participants and received over 1,600 submissions. Like the previous IJCAI-2022 Neural MMO Challenge, it involved agents from 16 populations surviving
Externí odkaz:
http://arxiv.org/abs/2311.03707
Reconfigurable Intelligent Surface (RIS) or metasurface is one of the important enabling technologies in mobile cellular networks that can effectively enhance the signal coverage performance in obstructed regions, and it is generally deployed on surf
Externí odkaz:
http://arxiv.org/abs/2311.01919
Autor:
Chen, Yangkun, Suarez, Joseph, Zhang, Junjie, Yu, Chenghui, Wu, Bo, Chen, Hanmo, Zhu, Hengman, Du, Rui, Qian, Shanliang, Liu, Shuai, Hong, Weijun, He, Jinke, Zhang, Yibing, Zhao, Liang, Zhu, Clare, Togelius, Julian, Mohanty, Sharada, Chen, Jiaxin, Li, Xiu, Zhu, Xiaolong, Isola, Phillip
We present the results of the second Neural MMO challenge, hosted at IJCAI 2022, which received 1600+ submissions. This competition targets robustness and generalization in multi-agent systems: participants train teams of agents to complete a multi-t
Externí odkaz:
http://arxiv.org/abs/2308.15802
As a challenging multi-player card game, DouDizhu has recently drawn much attention for analyzing competition and collaboration in imperfect-information games. In this paper, we propose PerfectDou, a state-of-the-art DouDizhu AI system that dominates
Externí odkaz:
http://arxiv.org/abs/2203.16406
Autor:
Kanervisto, Anssi, Milani, Stephanie, Ramanauskas, Karolis, Topin, Nicholay, Lin, Zichuan, Li, Junyou, Shi, Jianing, Ye, Deheng, Fu, Qiang, Yang, Wei, Hong, Weijun, Huang, Zhongyue, Chen, Haicheng, Zeng, Guangjun, Lin, Yue, Micheli, Vincent, Alonso, Eloi, Fleuret, François, Nikulin, Alexander, Belousov, Yury, Svidchenko, Oleg, Shpilman, Aleksei
Reinforcement learning competitions advance the field by providing appropriate scope and support to develop solutions toward a specific problem. To promote the development of more broadly applicable methods, organizers need to enforce the use of gene
Externí odkaz:
http://arxiv.org/abs/2202.10583
Exploration is crucial for training the optimal reinforcement learning (RL) policy, where the key is to discriminate whether a state visiting is novel. Most previous work focuses on designing heuristic rules or distance metrics to check whether a sta
Externí odkaz:
http://arxiv.org/abs/2201.11685
Neural architecture search (NAS) has shown encouraging results in automating the architecture design. Recently, DARTS relaxes the search process with a differentiable formulation that leverages weight-sharing and SGD where all candidate operations ar
Externí odkaz:
http://arxiv.org/abs/2201.11679
Akademický článek
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Publikováno v:
In Journal of Stroke and Cerebrovascular Diseases December 2021 30(12)
Akademický článek
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