STCL using G-MAPPO prevents policy stagnation in UAV networks, recovering reliability above 0.9 for up to 100 users and delivering 20% capacity gain under high loads versus MADDPG.
Identifi- cation of tidal-traffic patterns in metro-area mobile netwo rks via matrix factorization based model
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Spatiotemporal Continual Learning for Mobile Edge UAV Networks: Mitigating Catastrophic Forgetting
STCL using G-MAPPO prevents policy stagnation in UAV networks, recovering reliability above 0.9 for up to 100 users and delivering 20% capacity gain under high loads versus MADDPG.