Zobrazeno 1 - 10
of 4 145
pro vyhledávání: '"Jin, Yue"'
Autor:
Tian, Sheng, Zeng, Xintan, Hu, Yifei, Wang, Baokun, Liu, Yongchao, Jin, Yue, Meng, Changhua, Hong, Chuntao, Zhang, Tianyi, Wang, Weiqiang
Graph-based patterns are extensively employed and favored by practitioners within industrial companies due to their capacity to represent the behavioral attributes and topological relationships among users, thereby offering enhanced interpretability
Externí odkaz:
http://arxiv.org/abs/2411.06878
Traditional offline reinforcement learning methods predominantly operate in a batch-constrained setting. This confines the algorithms to a specific state-action distribution present in the dataset, reducing the effects of distributional shift but res
Externí odkaz:
http://arxiv.org/abs/2405.14374
In the existing software development ecosystem, security issues introduced by third-party code cannot be overlooked. Among these security concerns, memory access vulnerabilities stand out prominently, leading to risks such as the theft or tampering o
Externí odkaz:
http://arxiv.org/abs/2310.06435
Publikováno v:
Machine Learning (ECML-PKDD 2023 Journal Track)
Offline reinforcement learning (RL) aims to infer sequential decision policies using only offline datasets. This is a particularly difficult setup, especially when learning to achieve multiple different goals or outcomes under a given scenario with o
Externí odkaz:
http://arxiv.org/abs/2303.09367
Multi-agent reinforcement learning (MARL) has achieved great progress in cooperative tasks in recent years. However, in the local reward scheme, where only local rewards for each agent are given without global rewards shared by all the agents, tradit
Externí odkaz:
http://arxiv.org/abs/2302.09277
Autor:
Zhang, Yinjie1,2 (AUTHOR) zhyj@sxu.edu.cn, Jin, Yue1,2 (AUTHOR) jinyueyaoyao@163.com, Wang, Yanjing1 (AUTHOR) wangyanjing@sjtu.edu.cn, Wang, Siyi1 (AUTHOR) wangsiyi_sjtu@163.com, Niu, Yuchen1 (AUTHOR) nyc123@sjtu.edu.cn, Ma, Buyong1 (AUTHOR) mabuyong@sjtu.edu.cn, Li, Jingjing1 (AUTHOR) lijj@sjtu.edu.cn
Publikováno v:
International Journal of Molecular Sciences. Oct2024, Vol. 25 Issue 19, p10857. 12p.
Flocking control is a significant problem in multi-agent systems such as multi-agent unmanned aerial vehicles and multi-agent autonomous underwater vehicles, which enhances the cooperativity and safety of agents. In contrast to traditional methods, m
Externí odkaz:
http://arxiv.org/abs/2209.08351
Flocking control is a challenging problem, where multiple agents, such as drones or vehicles, need to reach a target position while maintaining the flock and avoiding collisions with obstacles and collisions among agents in the environment. Multi-age
Externí odkaz:
http://arxiv.org/abs/2209.08347
Learning to coordinate is a daunting problem in multi-agent reinforcement learning (MARL). Previous works have explored it from many facets, including cognition between agents, credit assignment, communication, expert demonstration, etc. However, les
Externí odkaz:
http://arxiv.org/abs/2205.11163
Autor:
Jin, Yue, Wang, Pengcheng
Publikováno v:
In International Review of Financial Analysis November 2024 96 Part B