Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
What are the Statistical Limits of Offline RL with Linear Function Approximation?
Authors: Ruosong Wang, Dean Foster, Sham M. Kakade
ICLR 2021 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Perhaps surprisingly, our main result shows that even if: i) we have realizability in that the true value function of every policy is linear in a given set of features and 2) our off-policy data has good coverage over all features (under a strong spectral condition), any algorithm still (information-theoretically) requires a number of ofο¬ine samples that is exponential in the problem horizon to nontrivially estimate the value of any given policy. |
| Researcher Affiliation | Collaboration | Ruosong Wang Carnegie Mellon University EMAIL Dean P. Foster University of Pennsylvania and Amazon EMAIL Sham M. Kakade University of Washington, Seattle and Microsoft Research EMAIL |
| Pseudocode | Yes | Algorithm 1 Least-Squares Policy Evaluation |
| Open Source Code | No | The paper does not provide any statement or link indicating the release of open-source code for the methodology described. |
| Open Datasets | No | The paper constructs theoretical |
| Dataset Splits | No | The paper is theoretical and does not involve empirical validation on datasets requiring explicit train/validation/test splits. |
| Hardware Specification | No | The paper is theoretical and does not describe any hardware used for experiments. |
| Software Dependencies | No | The paper is theoretical and does not describe specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and focuses on statistical limits and algorithm analysis, not on empirical experiment setup with hyperparameters. |