HDRL-MoE is a hierarchical DRL framework with MoE that decouples slow inference decisions from fast UAV trajectory control in a constrained POMDP to maximize inference accuracy under mission constraints.
Joint AI inference and target tracking at network edge: A hybrid offline-online design for UA V- enabled network
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.NI 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
UAV-Assisted Cooperative Edge Inference for Low-Altitude Economy via MoE-based Hierarchical Deep Reinforcement Learning
HDRL-MoE is a hierarchical DRL framework with MoE that decouples slow inference decisions from fast UAV trajectory control in a constrained POMDP to maximize inference accuracy under mission constraints.