AOS-Bench tests how AI agents handle multiple tasks at once
Researchers introduced AOS-Bench, a new benchmark for evaluating AI agents as persistent workload managers. Unlike existing tests, it measures how agents handle overlapping tasks—such as builds, data processing, and bug fixes—under shared CPU and memory constraints. The benchmark shows that success rates vary widely: on heavy workloads, systems lose 13 to 23 points, while on medium workloads,…
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Key points
- AOS-Bench evaluates AI agents managing overlapping tasks under CPU/memory limits, unlike isolated benchmarks
- Systems lose 13–23 points on heavy workloads and show 11–26 point gaps in stream success rates
- Task intake policies matter most: serial dispatch leaves 73% of heavy tasks unclaimed, but fixed concurrency nearly matches best policies
Read the original at arXiv cs.AI · by Erle Zhu, Genrui Zhang, Keyang Hu, Mingyu Su, Hongning Wang primary sourceOpen source ↗
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