Sample-efficient multi-agent reinforcement learning with masked reconstruction

Deep reinforcement learning (DRL) is a powerful approach that combines reinforcement learning (RL) and deep learning to address complex decision-making problems in high-dimensional environments. Although DRL has been remarkably successful, its low sample efficiency necessitates extensive training ti...

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