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AI Agent Swarms as Researchers: Progress, Challenges, and Open Questions — arXiv:2609.35719

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.35719
License (as archived): CC0-1.0
Archived: 2026-10-07T22:13:43.725Z
SHA-256 of the archived text: fc65a2803adeb04ac837c9cb55fbfa96fe37062bbf50dec3b6bc4a30e3ff3356
Stable URL of this page: https://metraipolis.com/documento/dc_d200fa9c19cb

How to cite

AI Agent Swarms as Researchers: Progress, Challenges, and Open Questions — arXiv:2609.35719 — arXiv (en), https://arxiv.org/abs/2609.35719 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_d200fa9c19cb (Metraipolis archive dc_d200fa9c19cb, sha256 fc65a2803adeb04ac837c9cb55fbfa96fe37062bbf50dec3b6bc4a30e3ff3356)

BibTeX

@misc{dcd200fa9c19cb,
  title = {AI Agent Swarms as Researchers: Progress, Challenges, and Open Questions — arXiv:2609.35719},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.35719},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_d200fa9c19cb; sha256 fc65a2803adeb04ac837c9cb55fbfa96fe37062bbf50dec3b6bc4a30e3ff3356},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.35719. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Artificial intelligence (AI) agents, language models connected to tools and run in a loop, can now carry out long, multi-step tasks with little supervision. We gave swarms of off-the-shelf coding agents a short statement of scope, from a narrow topic to a whole field, access to the literature and to computing tools, and one standing instruction: make real, correct, useful progress, and do not stop. We supplied no scientific ideas. Within weeks, the agents produced a large body of research notes, paper-length drafts, and formal proofs in five areas of optimization theory and physical science, and proposed untested laboratory experiments in a sixth. We do not claim that all of it is correct or new, but it is not noise: in what we have checked so far, we found no major scientific error, and several results are proved in a proof assistant. The agents produced results faster than we could review them; we estimate that a full review would take us months. Together with two widely discussed 2026 results in mathematics obtained with swarms, our runs suggest that agents can already do a large part of routine theoretical research, at least in areas that we experimented with. This raises questions we cannot yet answer: how to trust results when review, not production, is the scarce resource; what credit and publication counts mean when the human input is a prompt, and why institutions would pay researchers rather than buy computing time; and how people can learn a field, add to what agents do, and stay in control of research they cannot keep up with. Research institutions are not ready: models improve faster than institutions change, so they should decide now how to respond as capabilities increase. We offer tentative positions, release the agents' unedited output as of 25 September 2026, and invite readers to repeat the experiment in their own fields.

Tema degli esploratori: governance digitale e beni comuni (retro-catalogo arXiv: annunci del 2026-09-29 in cs.CY).
Categorie arXiv: Computers and Society (cs.CY).
Pagina del lavoro: https://arxiv.org/abs/2609.35719 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-07T21:55:04.255Z dalla pagina https://arxiv.org/catchup/cs.CY/2026-09-29?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).