基本信息
浏览量:188
职业迁徙
个人简介
Main Research Interests
Multi-Agent Systems
Yong focuses on simplification of learning process in multi-agent systems, i.e., game abstraction.
The large number of agents and complex game relationship cause great difficulty for policy learning. Therefore, simplifying the learning process is an important research issue.
Reinforcement Learning
Yong focuses on the algorithm framework of reinforcement learning and applications, especially in multi-agent systems. Reinforcement learning learn the policy through the feedback from environment, which is a way closer to the human model. I'm really interested in it.
Transfer Learning
Yong focuses on the transfer learning in multi-agent systems, especially between environments with different number of agents. Policy learning is difficult in large-scale multi-agent systems. We use incremental learning and teansfer learning to solve the problem.
研究兴趣
论文共 21 篇作者统计合作学者相似作者
按年份排序按引用量排序主题筛选期刊级别筛选合作者筛选合作机构筛选
时间
引用量
主题
期刊级别
合作者
合作机构
arxiv(2024)
arxiv(2024)
引用0浏览0引用
0
0
International Conference on Learning Representations (ICLR) (2022)
引用11浏览0EI引用
11
0
AAAI Conference on Artificial Intelligenceno. 8 (2022): 8779-8787
引用52浏览0EI引用
52
0
加载更多
作者统计
合作学者
合作机构
D-Core
- 合作者
- 学生
- 导师
数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn