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Multi-Agent Reinforcement Learning for Autonomous UAV Exploration in Wildfire Response
This study develops a deep reinforcement learning framework for training Unmanned Aerial Vehicle (UAV) agents to navigate and monitor simulated wildfire environments. Results show that agents learn increasingly stable and effective behaviors over time, as demonstrated by converging loss trends, impr
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