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Before Agents Decide: Epistemic Action in LLM-Based Systems — arXiv:2610.00511

Source: arXiv (en)
Original: https://arxiv.org/abs/2610.00511
License (as archived): CC0-1.0
Archived: 2026-10-06T11:54:31.400Z
SHA-256 of the archived text: def7a3bd22649b7fea07f24f6cf9dbf9575a04b4c44618c78936d9f0ff648b29
Stable URL of this page: https://metraipolis.com/documento/dc_855271ea0e72

How to cite

Before Agents Decide: Epistemic Action in LLM-Based Systems — arXiv:2610.00511 — arXiv (en), https://arxiv.org/abs/2610.00511 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_855271ea0e72 (Metraipolis archive dc_855271ea0e72, sha256 def7a3bd22649b7fea07f24f6cf9dbf9575a04b4c44618c78936d9f0ff648b29)

BibTeX

@misc{dc855271ea0e72,
  title = {Before Agents Decide: Epistemic Action in LLM-Based Systems — arXiv:2610.00511},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2610.00511},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_855271ea0e72; sha256 def7a3bd22649b7fea07f24f6cf9dbf9575a04b4c44618c78936d9f0ff648b29},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2610.00511. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Before a difficult decision, people often act simply to understand the situation better. We turn an object to see another side, place alternatives next to each other, or change one condition and observe what happens. These actions may not complete the task, but they improve the evidence needed for the next choice. LLM-based agents can search and explore, yet agent design gives less attention to an earlier question: is the available evidence ready for the decision? Sometimes necessary evidence is missing. In other cases, the evidence is present but its form hides what matters, or the comparison needed to judge it does not yet exist. Cognitive science calls actions that improve the basis for a later choice epistemic actions. We bring this idea to LLM-based agents and distinguish three modes: acquiring missing evidence, transforming available evidence, and probing a system to create a revealing response. We use the term epistemic scaffolding for the interfaces, tools, and environments that make these actions possible and auditable. This paper argues that agent design must address how decision-ready evidence is produced.

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-10-02 in cs.MA).
Categorie arXiv: Artificial Intelligence (cs.AI) ; Multiagent Systems (cs.MA).
Pagina del lavoro: https://arxiv.org/abs/2610.00511 — 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 2026-10-06T10:17:30.555Z dalla pagina https://arxiv.org/catchup/cs.MA/2026-10-02?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).