Learning to Share in Multi-Agent Reinforcement Learning

2 code implementations • 16 Dec 2021 • Yuxuan Yi, Ge Li, YaoWei Wang, Zongqing Lu

Inspired by the fact that sharing plays a key role in human's learning of cooperation, we propose LToS, a hierarchically decentralized MARL framework that enables agents to learn to dynamically share reward with neighbors so as to encourage agents to cooperate on the global objective through collectives.

Multi-agent Reinforcement Learning reinforcement-learning +1