A multi-agent reinforcement learning framework for optimizing coverage and connectivity in Space-Air-Ground integrated networks. This project simulates and trains intelligent agents to coordinate satellites, UAVs, and ground stations for efficient network deployment.
☆56Feb 26, 2026Updated last month
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