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Publications: Ferrer-Mestres, J., Dietterich, T. G., Buffet, O., & Chades, I. (2020, June). Solving k-mdps. In Proceedings of the International Conference on Automated Planning and Scheduling (Vol. 30, pp. 110
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to avoid system bottlenecks, and ensuring low-latency performance. Energy-Efficient Operations with Carbon-Aware Scheduling: Example: For non-urgent data processing, SmartScaleSys (S3) could prioritize tasks
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intelligent techniques for scheduling and offloading tasks to the cloud and peer vehicles. This will ultimately meet the Quality of Service (QoS) requirements of time-critical road safety applications and
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levels for manufacturing, routing delivery trucks for transport, scheduling power stations and electricity grids, to name just a few. In recent years, deep learning is showing startling ability
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-time, with flexible schedules depending on the type and duration of student placements. Practice educators have access to professional development activities that support further development