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Dataset · Hugging Face

villekuosmanen/dAgger_build_block_tower_1.2.0-advantages

Advantage Values for villekuosmanen/dAgger_build_block_tower_1.2.0 Pre-computed advantage values for offline RL training. Source Dataset: villekuosmanen/dAgger_build_block_tower_1.2.0 Value Model: villekuosmanen/rewact_build_block_tower_all_3 N-step lookahead: 50 Files This dataset contains per-episode parquet files with advantage values for each frame. Usage from pathlib import Path import pandas as pd # Load advantages for a… See the full description on the dataset page: https://huggingface.co/datasets/villekuosmanen/dAgger_build_block_tower_1.2.0-advantages.

Author / organizationvillekuosmanen
License (as declared)apache-2.0
Downloads206 (as reported by Hugging Face)
Likes0
Created12 December 2025
Last updated at source22 March 2026
advantagereinforcement-learningrewact
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  • 17 Oct 2026 Description: Advantage Values for villekuosmanen/dAgger_build_block_tower_1.2.0 Pre-computed advantage values for offline RL training. Source Dataset: villekuosmanen/dAgger_build_block_tower_1.2.0 Value Model: villekuosmanen/rewact_build_block_tower_all → Advantage Values for villekuosmanen/dAgger_build_block_tower_1.2.0 Pre-computed advantage values for offline RL training. Source Dataset: villekuosmanen/dAgger_build_block_tower_1.2.0 Value Model: villekuosmanen/rewact_build_block_tower_all

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