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cs.AI2025
Adaptive Approach to Enhance Machine Learning Scheduling Algorithms During Runtime Using Reinforcement Learning in Metascheduling Applications
Samer Alshaer, Ala Khalifeh, Roman Obermaisser
Metascheduling in time-triggered architectures has been crucial in adapting to dynamic and unpredictable environments, ensuring the reliability and efficiency of task execution. Ho…
cs.AI2025
Reconstruction-Based Adaptive Scheduling Using AI Inferences in Safety-Critical Systems
Samer Alshaer, Ala Khalifeh, Roman Obermaisser
Adaptive scheduling is crucial for ensuring the reliability and safety of time-triggered systems (TTS) in dynamic operational environments. Scheduling frameworks face significant c…