GLo-MAPPO applies centralized-training decentralized-execution MAPPO with a gain-based association scheme to jointly optimize LoRa parameters and UAV paths, yielding higher weighted energy efficiency than prior MARL baselines in simulations.
Bench- marking multi-agent deep reinforcement learning algorithms in coopera- tive tasks,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.NI 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
GLo-MAPPO: Multi-Agent Deep Reinforcement Learning for Energy-Efficient UAV-Assisted LoRa Networks
GLo-MAPPO applies centralized-training decentralized-execution MAPPO with a gain-based association scheme to jointly optimize LoRa parameters and UAV paths, yielding higher weighted energy efficiency than prior MARL baselines in simulations.