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Sprint projectOct 25, 2026Hong Kong

Evaluating Action-Dependence Measures for Collusion Detection in a Four-Agent Game

Benjamin Harris Chen Tia

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

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An auditor who sees two agents acting in step may be seeing collusion, or something innocent. We study that gap in a four-player version of rock-paper-scissors, using scripted simulations and decisions from one small local language model. Two players can look linked because both follow the same public cue, and when the auditor cannot see that cue the innocent pair can outrank a deliberately linked pair. We calculate where that reversal happens, how small samples shift it, and why independent calibration transfers badly. In the recorded games a message alone changed no action, some replies copied the sender instead of executing the request, and naming the exact target worked in 179/180 later seeded cases. Exact payoff enumeration and matched replay show no average harm to the two outsiders, because three different symbols reward everyone. We claim no spontaneous collusion and no general detector; an alarm should only start an investigation.

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Cite this project

@misc{tia2026evaluating,
  title = {{Evaluating Action-Dependence Measures for Collusion Detection in a Four-Agent Game}},
  author = {Benjamin Harris Chen Tia},
  year = {2026},
  month = oct,
  note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/evaluating-actiondependence-measures-for-collusion-detection-in-a-fouragent-game-4l85}},
  url = {https://apartresearch.com/sprints/projects/evaluating-actiondependence-measures-for-collusion-detection-in-a-fouragent-game-4l85}
}

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