Preprint
Aug 2026
CoDrift: Compositional Drifting for Offline Reinforcement Learning
This work proposes CoDrift, a compositional framework for one-step generative policy learning that combines three objective-level fields into a unified policy field that compares favorably with state-of-the-art methods and achieves the best average rank in both settings.
Xiewei Ni, Ruo-Syuan Mei, Xiangyu Xu
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