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.
On transforming reinforcement learning with transformers: The development trajectory.IEEE Transactions on Pattern Analysis and Machine Intelligence, 46 (12):8580–8599, 2024
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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.