What is recorded here?
Modified rewards in a learned dynamics model by an uncertainty penalty and optimized policies in the penalized MDP, connecting conservative model use to conditional return bounds.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
The lower-bound analysis requires an admissible model-error estimator and stated value-class assumptions, not merely a learned variance heuristic. Exact surrogate optimization differs from finite deep RL updates. This soft reward-penalty mechanism is distinct from MOReL's unknown-region absorbing state.
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People and systems
Tianhe Yu; Garrett Thomas; Lantao Yu; Stefano Ermon; James Zou; Sergey Levine; Chelsea Finn; Tengyu Ma
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.
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English catalogue narrative
MOPO: uncertainty-penalized learned MDPs for offline policy optimization
Modified rewards in a learned dynamics model by an uncertainty penalty and optimized policies in the penalized MDP, connecting conservative model use to conditional return bounds.
Scientific scope
The lower-bound analysis requires an admissible model-error estimator and stated value-class assumptions, not merely a learned variance heuristic. Exact surrogate optimization differs from finite deep RL updates. This soft reward-penalty mechanism is distinct from MOReL's unknown-region absorbing state.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Tianhe Yu; Garrett Thomas; Lantao Yu; Stefano Ermon; James Zou; Sergey Levine; Chelsea Finn; Tengyu Ma
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.