17 citations · 20 across the 5 of their papers we have counts for
5 papers
Causal Mean Field Multi-Agent Reinforcement Learning
Hao Ma, Zhiqiang Pu, Yi Pan +3
Scalability remains a challenge in multi-agent reinforcement learning and is currently under active research. A framework named mean-field reinforcement learning (MFRL) could allev…
Learning Heterogeneous Agent Cooperation via Multiagent League Training
Qingxu Fu, Xiaolin Ai, Jianqiang Yi +3
Many multiagent systems in the real world include multiple types of agents with different abilities and functionality. Such heterogeneous multiagent systems have significant practi…
A Cooperation Graph Approach for Multiagent Sparse Reward Reinforcement Learning
Qingxu Fu, Tenghai Qiu, Zhiqiang Pu +2
Multiagent reinforcement learning (MARL) can solve complex cooperative tasks. However, the efficiency of existing MARL methods relies heavily on well-defined reward functions. Mult…
Characterizing player's playing styles based on Player Vectors for each playing position in the Chinese Football Super League
Yuesen Li, Shouxin Zong, Yanfei Shen +3
Characterizing playing style is important for football clubs on scouting, monitoring and match preparation. Previous studies considered a player's style as a combination of technic…
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…