Reserve-Aware Contrast Certificates for Conservative Bandits with Uncertain Baselines

Abstract:Conservative bandits must improve an incumbent policy without exhausting a prescribed performance budget. When the incumbent is uncertain, separately bounding candidate and baseline rewards can charge twice for shared estimation error. We develop Reserve-C4B around the baseline-relative contrast itself. A shared confidence set yields an exact expression for this avoidable penalty and a tighter admissibility test at every fixed history. A reserve ledger separates statistical evidence from permitted performance deficit; a prefix-refresh extension recertifies accumulated decisions under the current confidence set without discarding previously certified credit. For linear rewards, self-normalized confidence sets provide simultaneous validity over time and adaptively generated candidates, and the resulting policy satisfies a conditional-mean performance constraint with high probability. Reproducible experiments isolate certificate coupling, prefix refresh, and historical information, showing large reductions in baseline fallback while exposing the limitations of frozen certificates.

Artificial Intelligence (cs.AI); Machine Learning (cs.LG)

arXiv:2609.39106 [cs.AI]

(or arXiv:2609.39106v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2609.39106 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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