Abstract: Reinforcement learning has increasingly showcased its potential in decision-making for the autonomous operation of urban rail transit. However, the inability of reinforcement learning to ...
Abstract: In this paper, we propose practical model-based policy optimization (PMBPO) to address the time efficiency issue caused by overly frequent model updates in recent probabilistic model-based ...
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