Bioeconomic Terrarium: Detecting Collusion Through Antitrust Plus Factors in a Thermodynamically Sealed Multi-Agent Economy
Akanksha Gupta · Team 3am Labs
Submitted to AI Collusion Research Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.
Detecting hidden collusion among autonomous AI agents executing sub-threshold micro-transactions is a critical safety blind spot. This paper adapts antitrust law’s legal "plus factors" into a six-rung computational evidence ladder operating entirely on pairwise transfer ledgers.
Tested inside Terrarium: a thermodynamically sealed, biomimetic ant-colony economy running Qwen 2.5 72B agents with zero market framing, every single experimental run successfully detected structural collusion (Rung 3 or 4). The study upends conventional safety assumptions: agents die from distribution failure while over half of system energy sits unallocated, cooperative alignment paradoxically amplifies collusion signals, and live surveillance is outperformed by cross-referencing dying agents' exit testimony ("Death Cards") against transfer ledgers. This delivers a low-cost, highly scalable blueprint for multi-agent forensics.
Keywords: AI collusion detection, evidence standards, multi-agent forensics, antitrust plus factors, biomimetic economics, AI safety
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@misc{gupta2026bioeconomic,
title = {{Bioeconomic Terrarium: Detecting Collusion Through Antitrust Plus Factors in a Thermodynamically Sealed Multi-Agent Economy}},
author = {Akanksha Gupta},
year = {2026},
month = oct,
note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
howpublished = {\url{https://apartresearch.com/sprints/projects/bioeconomic-terrarium-detecting-collusion-through-antitrust-plus-factors-in-a-thermodynamically-sealed-multiagent-economy-njub}},
url = {https://apartresearch.com/sprints/projects/bioeconomic-terrarium-detecting-collusion-through-antitrust-plus-factors-in-a-thermodynamically-sealed-multiagent-economy-njub}
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