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Bellman Calibration for Marginalized Importance Weighting in Offline Reinforcement Learning

This story is from 2026-08-26. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2608.24858v1 Announce Type: cross Abstract: Marginalized importance weighting evaluates a target policy by reweighting offline state-action samples with its discounted occupancy ratio, characterized by an adjoint Bellman equation. Existing minimax, primal-dual, and fitted fixed-point estimato…

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  1. 2026-08-26 04:00 · arXiv stat.ML
    Bellman Calibration for Marginalized Importance Weighting in Offline Reinforcement Learning

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