AWhat changed
Replayed trajectories with alternative achieved goals and recomputed goal-dependent rewards, allowing off-policy goal-conditioned agents to learn from attempts that missed the requested goal.
Scientific scope
Replayed trajectories with alternative achieved goals and recomputed goal-dependent rewards, allowing off-policy goal-conditioned agents to learn from attempts that missed the requested goal. Assumes goals can be represented and achieved goals identified, reward recomputation is available, and goals do not change environment transition dynamics. Not reward-free learning or arbitrary-task hindsight optimization. Unbiased relabeling is not established for arbitrary stochastic settings.
Evidence
The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Assumes goals can be represented and achieved goals identified, reward recomputation is available, and goals do not change environment transition dynamics. Not reward-free learning or arbitrary-task hindsight optimization. Unbiased relabeling is not established for arbitrary stochastic settings.
Contributors
- Source-listed authors and technical contributors · SCIENCE: Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.
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