Robust and Learned Online Matching in Growing Trees
We study irrevocable maximum-cardinality matching in trees revealed by successive leaf attachments, with a known horizon and an exogenous growth law that is misspecified or unknown. For deterministic affine attachment forecasts with nonnegative degree reinforcement, the optimal threshold policy loses at most twice the cumulative expected conditional total-variation error relative to an online oracle knowing the actual growth law. This follows from a unit-span property of the Bellman continuation score and has no additional horizon factor. A four-vertex example attains the coefficient two for the specified deterministic policy, and a two-model argument gives a lower bound linear in the mod...
| Authors | Marek Gałązka, Hanna Wdowicka |
|---|---|
| Primary category | cs.DS |
| Published | 30 September 2026 |
| Last updated at source | 30 September 2026 |
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