Uncertainty-Aware Resource Orchestration for Agentic AI Systems
4.40T1 sourcearXiv cs.MA
Source record
Published by arXiv cs.MA (T1 source). The original is at https://arxiv.org/abs/2611.05392.
Pipeline notes
The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.
SummaryThe paper formalizes resource allocation for multi-step LLM agents whose compute, bandwidth, and latency demands emerge at runtime. It proposes Conformal Reservation for Orchestration, using prior execution traces and conformal prediction to meet deadlines with probabilistic guarantees while limiting over-reservation. Simulations report lower resource waste than a coverage-feasible baseline.
Why it mattersProvides a testable scheduling method for operating agents under uncertain demand, with reported coverage and resource-efficiency comparisons useful for infrastructure planning.
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