Mar, 2024
大规模异构多智能体系统的优先级强化学习
Prioritized League Reinforcement Learning for Large-Scale Heterogeneous
Multiagent Systems
TL;DR提出了一种名为PHLRL(Prioritized Heterogeneous League Reinforcement Learning)的方法,用于解决大规模异构合作问题,并使用LSMO(Large-Scale Multiagent Operation)基准测试显示PHLRL优于QTRAN和QPLEX等现有方法。