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Sprint projectOct 25, 2026Mississauga, ON, Canada

Knocking on a Locked Door: What Monitors Can See When Colluding Agents Cannot Talk

Aaron Alva

Submitted to AI Collusion Research Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.

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When colluding AI agents cannot exchange messages, a text monitor has nothing to read. We asked what a monitor can still detect. Building on the Colosseum framework, we modified a four-agent ticket-allocation task so agents publicly mark tentative choices each round, then ran 629 games across four models (GPT-4o-mini, GPT-4.1-mini, Gemini 2.5 Flash, Claude Haiku 4.5) with matched control pairs. Only GPT-4.1-mini coalitions gained from colluding, and only when they could talk privately; no model gained from actions alone, and harsher "scheme against them" prompts made collusion worse. LLM judges reading messages or actions performed near chance. The one decisive signal was failed attempts to message through a blocked channel, which caught every GPT-4o-mini coalition, but none of the three stronger models ever tried. The coalitions that gave themselves away were the ones that didn't matter.

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Cite this project

@misc{alva2026knocking,
  title = {{Knocking on a Locked Door: What Monitors Can See When Colluding Agents Cannot Talk}},
  author = {Aaron Alva},
  year = {2026},
  month = oct,
  note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/knocking-on-a-locked-door-what-monitors-can-see-when-colluding-agents-cannot-talk-psi6}},
  url = {https://apartresearch.com/sprints/projects/knocking-on-a-locked-door-what-monitors-can-see-when-colluding-agents-cannot-talk-psi6}
}

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