Evidence of Collusion between AI Agent Sellers in an Elastic Market
Ann Li, Mandy Liang, Raymond Yeung, Nathan Wong · Team Canons
Submitted to AI Collusion Research Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.
This research proposes a decision rule for an elastic pricing duopoly with two AI agent sellers. An experiment was designed to stimulate the market operation, and each trajectory of the conversation and tool calling of the LLM sellers was judged by a core score, which is equal to the average of three signals: conversation pattern, dependence evidence and coalition advantage. These signals were translated into a mathematical expression as a judge score to determine the scenario of the trajectories based on our case hypothesis classification defined in Methodology. For the results and findings, the market structure was simulated, and one round of outputs was generated. However, those outputs were not verified or analysed due to time limitations. The contribution is therefore a testable evidentiary framework, not a demonstrated finding of collusion.
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Cite this project
@misc{li2026evidence,
title = {{Evidence of Collusion between AI Agent Sellers in an Elastic Market}},
author = {Ann Li and Mandy Liang and Raymond Yeung and Nathan Wong},
year = {2026},
month = oct,
note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
howpublished = {\url{https://apartresearch.com/sprints/projects/evidence-of-collusion-between-ai-agent-sellers-in-an-elastic-market-11j9}},
url = {https://apartresearch.com/sprints/projects/evidence-of-collusion-between-ai-agent-sellers-in-an-elastic-market-11j9}
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