Theoretical computer science·OpenAI Math·Result 111·Lean formalisation listed

One-sample matroid prophet inequalities against an almighty adversary

One of the 372 results in OpenAI's public mathematics catalogue, filed under theoretical computer science: 1 preprint, the latest dated 23 September 2026. This page quotes OpenAI's own summary of the claim, links the paper and abstract, and will embed the animation.

Latest paper

One Sample Suffices for Matroid Prophet Inequalities against an Almighty Adversary

23 September 2026 · PDF

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What OpenAI claims

For every finite matroid known in advance, gives a distribution-independent online rule using one independent sample per element and earning a universal constant fraction of the expected offline optimum. Values are independent and nonnegative, with finite expected optimum. The guarantee holds even when the arrival-order adversary sees all samples, values, and the rule's entire random seed; no polynomial-time implementation is asserted. (Lean)

Paper

  1. One Sample Suffices for Matroid Prophet Inequalities against an Almighty Adversary

    · Preprint, not peer reviewed · PDF

    We prove that one independent sample per element suffices for a constant-competitive prophet inequality on every finite matroid. The guarantee holds even when the arrival-order adversary observes all samples, all online values, and the algorithm's entire random seed. The rule needs no description of the value distributions and achieves the absolute competitive ratio 2-310.

Status

Preprint. The paper has not been independently reviewed. Treat the result as OpenAI's claim until other mathematicians have checked it. If a video exists, it illustrates the statement; it is not the proof.

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