Abstract: Path planning in robotics and automation often demands solutions that effectively balance efficiency and path smoothness, particularly in diverse and large-scale environments. To address ...
Abstract: Model-free deep reinforcement learning has emerged as a promising method for addressing the scheduling challenges in integrated energy systems. However, uncertainty in system states ...
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