Showing 2024Show all
3 papers · 1 filter
cs.LG2024
Mean-Field Sampling for Cooperative Multi-Agent Reinforcement Learning
Emile Anand, Ishani Karmarkar, Guannan Qu
Designing efficient algorithms for multi-agent reinforcement learning (MARL) is fundamentally challenging because the size of the joint state and action spaces grows exponentially…
cs.LG2024
Efficient Reinforcement Learning for Global Decision Making in the Presence of Local Agents at Scale
Emile Anand, Guannan Qu
We study reinforcement learning for global decision-making in the presence of local agents, where the global decision-maker makes decisions affecting all local agents, and the obje…
cs.LG2024
Efficient Reinforcement Learning for Routing Jobs in Heterogeneous Queueing Systems
Neharika Jali, Guannan Qu, Weina Wang +1
We consider the problem of efficiently routing jobs that arrive into a central queue to a system of heterogeneous servers. Unlike homogeneous systems, a threshold policy, that rout…