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A Mobile Agent-Based Hierarchical Reinforcement Learning Framework for Energy-Balanced Data Collection and Wireless Charging in WSN
Energy imbalance remains a key challenge in Wireless Sensor Networks (WSNs), as nodes near the base station deplete their energy faster due to heavy forwarding loads. While mobile agents (MAs) have been employed for either data collection or sensor charging, existing approaches lack adaptability and
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