A closed-loop LLM framework generates and refines routing rewards for LEO satellite networks, matching an expert baseline within 3 percent goodput.
An open source multi-agent deep reinforce- ment learning routing simulator for satellite networks,
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LLM-Driven Automated Reward Design for Reinforcement Learning-Based Routing in LEO Satellite Networks
A closed-loop LLM framework generates and refines routing rewards for LEO satellite networks, matching an expert baseline within 3 percent goodput.