Search Results for author: William Steenbergen

Found 2 papers, 0 papers with code

Data-Efficient Pipeline for Offline Reinforcement Learning with Limited Data

no code implementations16 Oct 2022 Allen Nie, Yannis Flet-Berliac, Deon R. Jordan, William Steenbergen, Emma Brunskill

Inspired by statistical model selection methods for supervised learning, we introduce a task- and method-agnostic pipeline for automatically training, comparing, selecting, and deploying the best policy when the provided dataset is limited in size.

Model Selection Offline RL +2

Cannot find the paper you are looking for? You can Submit a new open access paper.