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Sprint projectOct 26, 2026

Three Checks Before Calling It Collusion: Competence, Chance and Incentive Audits of LLM Pricing Agents

Demchyna Oleh

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

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Report: Three Checks Before Calling It Collusion: Competence, Chance and Incentive Audits of LLM Pricing Agents

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We audited our own LLM-collusion benchmark and found it measured noise. A local Qwen3.5-9B passed a table-based qualification gate (12/12) yet chose strictly dominated actions at the uniform-random rate (16/20 vs 15.75); adding a payoff table cut errors to 6/20 (McNemar p = 0.002). In 21 preregistered Bertrand-duopoly games with a 70% collusion premium (15 labeled-table, 3 matrix-table, 3 formula-only), all 15 labeled-table games priced inside or below the uniform-random band; talk did not raise prices, and agents honoured their "both set 21" proposals in 10/49 cases. The matrix table put 3/3 games above that band (exact p = 0.012; mean price ≈ 19 vs Nash 15). On scripted ground truth, level-based screens flag high prices, not strategy; only an end-game test separates strategic collusion from unconditional cooperation. We provide a three-check audit protocol and raw token journals.

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Cite this project

@misc{oleh2026three,
  title = {{Three Checks Before Calling It Collusion: Competence, Chance and Incentive Audits of LLM Pricing Agents}},
  author = {Demchyna Oleh},
  year = {2026},
  month = oct,
  note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/three-checks-before-calling-it-collusion-competence-chance-and-incentive-audits-of-llm-pricing-agents-n1z9}},
  url = {https://apartresearch.com/sprints/projects/three-checks-before-calling-it-collusion-competence-chance-and-incentive-audits-of-llm-pricing-agents-n1z9}
}

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