Evolving Agent Teams
The rapid progress of software engineering agents drives interest in applying them to open-ended problems such as GPU kernel optimization. However, we find that existing coding agents converge to local optima on real-world, expert-written kernels (e.g., FlashInfer). We introduce Evolving Agent Teams, a multi-agent framework that escapes such local optima. It features (1) a central supervisor that diagnoses each local optimum and restructures a team of agents; and (2) a persistent file system that comprises a learning document, an evolution history, and per-team artifacts, grounding restructuring with accumulated experience. Under a matched token budget, Evolving Agent Teams consistently o...
| Authors | Shiyi Cao, Ziming Mao, Dacheng Li et al. |
|---|---|
| Primary category | cs.AI |
| Published | 27 October 2026 |
| Last updated at source | 27 October 2026 |
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