Jianzhun Shao

Credit Assignment with Meta-Policy Gradient for Multi-Agent Reinforcement Learning

2021 · arXiv (Cornell University)

Reward decomposition is a critical problem in centralized training with decentralized execution~(CTDE) paradigm for multi-agent reinforcement learning. To take full advantage of global information, which exploits the states from all agents and the related environment …