Distributed Routing for LEO Satellite Networks: A Multi-Agent Deep Reinforcement Learning Approach With State Information Lag
Multi-agent deep reinforcement learning (MADRL) offers a promising solution for routing in low Earth orbit (LEO) satellite networks. However, large inter-satellite propagation delays lead to severe state information lag in agent interactions, giving rise to decision biases and degraded routing timeliness. To this end,...