mahgoobi
scoring_data
A branch-and-rollback search dataset containing 650 searches across 13 tasks with 24,270 nodes, where multiple action chunks are proposed from each state and evaluated for their outcomes, including counterfactual rollbacks of abandoned branches.
Downloads0
Episodes650
Why This Matters for Physical AI
This dataset enables training of action scorers by providing counterfactual trajectory data showing what would have happened with different action choices, critical for learning robust action selection in robotic manipulation.
Technical Profile
- Modalities
- rgbstate
- Action Space
- action_chunks
- Environment
- simulation
- Task Types
- manipulationpick_and_placeobject_placement
- Episodes
- 650
- Data Format
- parquet
- Annotation Types
- action_labelsreward_labels
Access
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