GEMS-DQN is developed, a centralized discrete-action scheduling framework for coordinated task and charging decisions that combines the complementary effects of global information, conflict-aware learning, and bounded look-ahead search, while revealing the expected computation–performance trade-off of the centralized f...
Shan Dan, Meng Zhang, Dong-Ming Liu et al.· Algorithms· 0 citations
MSF-DETR is proposed, a multi-scale feature enhancement framework built on RT-DETR that integrates four coordinated components: an Enhanced Feature Connection module for adaptive cross-scale interaction, a Feature Channel Attention module for frequency-domain discriminative enhancement, a Reinforced Attention Feedback...
Shan Dan, Zan-Qi Qiu, Da-Di Cai et al.· Italian National Conference...· 0 citations
This paper proposes a trajectory-predictive and attention-enhanced deep recurrent State-Action-Reward-State-Action (SARSA) algorithm (PA-DR-SARSA), which incorporates future motion information into on-policy reinforcement learning through a Gated Recurrent Unit–based trajectory prediction module that learns temporal mo...
Shan Dan, Meng Zhang, Dong-Ming Liu et al.· Transactions of the Institut...· 0 citations
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