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Paper · arXiv

Correcting Within-Group Self-Selection Bias in Prioritized Replay

Prioritized experience replay (PER) improves sample efficiency by replaying high-priority transitions, usually according to absolute temporal-difference error. In stochastic environments, PER can distort the distribution of realized outcomes replayed from transitions with the same state-action pair. We call this within-group self-selection. We quantify the resulting changes in within-group outcome frequencies and mean Bellman targets. We decompose PER into between-group allocation and conditional sibling selection, and derive fixed-buffer corrections that preserve current group-level priority mass: SAMPLE selects a group through PER and trains on a uniformly sampled sibling; AVG averages ...

AuthorsOscar Miró López-Feliu, Herke van Hoof
Primary categorycs.LG
Published21 September 2026
Last updated at source21 September 2026
cs.LG
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