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arXiv · 2501.06339

On The Statistical Complexity of Offline Decision-Making

Thanh Nguyen-Tang·Raman Arora
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Abstract

We study the statistical complexity of offline decision-making with function approximation, establishing (near) minimax-optimal rates for stochastic contextual bandits and Markov decision processes. The performance limits are captured by the pseudo-dimension of the (value) function class and a new characterization of the behavior policy that \emph{strictly} subsumes all the previous notions of data coverage in the offline decision-making literature. In addition, we seek to understand the benefits of using offline data in online decision-making and show nearly minimax-optimal rates in a wide range of regimes.

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Thanh Nguyen-Tang, Raman Arora. 2025-01-10. On The Statistical Complexity of Offline Decision-Making. https://arxiv.org/abs/2501.06339

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