Derives K^*(N)=Θ(N^{α/(α+β)}) for optimal agent types in HMFG, with K^*(N)=Θ(N^{1/3}) for 1D queues and Θ(N^{1/5}) for 2D queue-channel models, plus performance gains over homogeneous baselines.
Heterogeneous mean-field multi-agent reinforcement learning for communication routing selection in sagi-net
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Heterogeneous Mean Field Game Framework for LEO Satellite-Assisted V2X Networks
Derives K^*(N)=Θ(N^{α/(α+β)}) for optimal agent types in HMFG, with K^*(N)=Θ(N^{1/3}) for 1D queues and Θ(N^{1/5}) for 2D queue-channel models, plus performance gains over homogeneous baselines.