TempoNet uses a slack-quantized Transformer with deep Q-learning and sparse attention to improve deadline fulfillment rates over traditional and neural schedulers in mixed-criticality real-time workloads.
Offline reinforcement learning with constrained hybrid action implicit representation towards wargaming decision-making.Tsinghua Science and Technology, 29(5):1422–1440
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TempoNet: Slack-Quantized Transformer-Guided Reinforcement Scheduler for Adaptive Deadline-Centric Real-Time Dispatchs
TempoNet uses a slack-quantized Transformer with deep Q-learning and sparse attention to improve deadline fulfillment rates over traditional and neural schedulers in mixed-criticality real-time workloads.