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novastar112/sokoban_hard_5box_remap_prev

VisGym sokoban_hard_5box Remap-Prev Solver-success Sokoban trajectories generated from the VisGym Sokoban environment. HF repo: https://huggingface.co/datasets/novastar112/sokoban_hard_5box_remap_prev task: sokoban_hard_5box env_id: sokoban/hard env_kwargs: {"action_mode": "move_only", "dim_room": [10, 10], "max_steps": 40, "num_boxes": 5, "num_gen_steps": 34, "success_mode": "stop_then_solved"} action schema: move-only ('move', 1..4) plus ('stop', 'stop') success semantics:… See the full description on the dataset page: https://huggingface.co/datasets/novastar112/sokoban_hard_5box_remap_prev.

sourceHugging Faceotherupdated 5mo agoView on Hugging Face

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VisGym sokobanhard5box Remap-Prev

Solver-success Sokoban trajectories generated from the VisGym Sokoban environment.

—HF repo: https://huggingface.co/datasets/novastar112/sokoban_hard_5box_remap_prev
—task: sokoban_hard_5box
—env_id: sokoban/hard
—envkwargs: `{"actionmode": "moveonly", "dimroom": [10, 10], "maxsteps": 40, "numboxes": 5, "numgensteps": 34, "successmode": "stopthen_solved"}`
—action schema: move-only ('move', 1..4) plus ('stop', 'stop')
—success semantics: stop_then_solved
—image policy: every history step has image_prev == image; the final step has image_next == image

The dataset is intended for the remap-prev training setup used by the Sokoban CE+MSE experiments.