25 citations · 90 across the 15 of their papers we have counts for
4 papers · 1 filter
Boosting Studies of Multi-Agent Reinforcement Learning on Google Research Football Environment: the Past, Present, and Future
Yan Song, He Jiang, Haifeng Zhang +3
Even though Google Research Football (GRF) was initially benchmarked and studied as a single-agent environment in its original paper, recent years have witnessed an increasing focu…
GCS: Graph-based Coordination Strategy for Multi-Agent Reinforcement Learning
Jingqing Ruan, Yali Du, Xuantang Xiong +6
Many real-world scenarios involve a team of agents that have to coordinate their policies to achieve a shared goal. Previous studies mainly focus on decentralized control to maximi…
Signal Instructed Coordination in Cooperative Multi-agent Reinforcement Learning
Liheng Chen, Hongyi Guo, Yali Du +7
In many real-world problems, a team of agents need to collaborate to maximize the common reward. Although existing works formulate this problem into a centralized learning with dec…
Bi-level Actor-Critic for Multi-agent Coordination
Haifeng Zhang, Weizhe Chen, Zeren Huang +4
Coordination is one of the essential problems in multi-agent systems. Typically multi-agent reinforcement learning (MARL) methods treat agents equally and the goal is to solve the…