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Sprint projectOct 26, 2026Saint-Petersburg

Adapting Standards-of-Proof Analysis to AI-Agent Collusion: A Wigmore-Based Interactive Evidence Graph

Alexander Rumyancev

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

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Report: Adapting Standards-of-Proof Analysis to AI-Agent Collusion: A Wigmore-Based Interactive Evidence Graph

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We built an interactive evidence graph for assessing whether a record shows collusion between AI agents. Evidence items pass admissibility and authenticity gates, receive an ordinal weight from 0 to 4, and aggregate into four elements under a weakest-link rule; the graph then reports the standard of proof the evidence meets. We compiled a base of twelve evidence types from recent published work and twelve case configurations, ran the graph on all of them, and released the graph, the dataset and the results publicly.

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  1. I like the idea of evaluating AI collusion by adapting legal standards of evidence. One feedback is to also incorporate real-world validation where possible. Also testing against actual agent traces and validating the scoring rules would make the work much stronger.

Cite this project

@misc{rumyancev2026adapting,
  title = {{Adapting Standards-of-Proof Analysis to AI-Agent Collusion: A Wigmore-Based Interactive Evidence Graph}},
  author = {Alexander Rumyancev},
  year = {2026},
  month = oct,
  note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/adapting-standardsofproof-analysis-to-aiagent-collusion-a-wigmorebased-interactive-evidence-graph-th1t}},
  url = {https://apartresearch.com/sprints/projects/adapting-standardsofproof-analysis-to-aiagent-collusion-a-wigmorebased-interactive-evidence-graph-th1t}
}

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