Weighted BC estimates trajectory density ratios from a clean reference set via binary discrimination and reweights the BC loss to converge to the clean expert policy with finite-sample bounds independent of contamination rate.
A survey on offline reinforcement learning: Taxonomy, review, and open problems.IEEE Transactions on Neural Networks and Learning Systems, 34(11):8043–8061, 2023
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Density-Ratio Weighted Behavioral Cloning: Learning Control Policies from Corrupted Datasets
Weighted BC estimates trajectory density ratios from a clean reference set via binary discrimination and reweights the BC loss to converge to the clean expert policy with finite-sample bounds independent of contamination rate.