Noise Distribution Decomposition based Multi-Agent Distributional Reinforcement Learning

no code implementations • 12 Dec 2023 • Wei Geng, Baidi Xiao, Rongpeng Li, Ning Wei, Dong Wang, Zhifeng Zhao

In this paper, we propose a novel decomposition-based multi-agent distributional RL method by approximating the globally shared noisy reward by a Gaussian mixture model (GMM) and decomposing it into the combination of individual distributional local rewards, with which each agent can be updated locally through distributional RL.

Distributional Reinforcement Learning Multi-agent Reinforcement Learning +3