4 citations · 5 across the 2 of their papers we have counts for
2 papers
cs.AI2022★ 4 cited
PTDE: Personalized Training with Distilled Execution for Multi-Agent Reinforcement Learning
Yiqun Chen, Hangyu Mao, Jiaxin Mao +5
Centralized Training with Decentralized Execution (CTDE) has emerged as a widely adopted paradigm in multi-agent reinforcement learning, emphasizing the utilization of global infor…
cs.AI2022★ 1 cited
Concentration Network for Reinforcement Learning of Large-Scale Multi-Agent Systems
Qingxu Fu, Tenghai Qiu, Jianqiang Yi +2
When dealing with a series of imminent issues, humans can naturally concentrate on a subset of these concerning issues by prioritizing them according to their contributions to moti…