ARC-RL: A Reinforcement Learning Playground Inspired by ARC Raiders
Paper • 2605.19503 • Published
Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 49, in _split_generators
import h5py
ModuleNotFoundError: No module named 'h5py'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 66, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
ARC-RL: A Reinforcement Learning Playground Inspired by ARC Raiders
This repository contains the expert demonstration datasets for ARC-RL, a suite of four MuJoCo continuous-control environments featuring robotic morphologies inspired by the game ARC Raiders.
- Paper: ARC-RL: A Reinforcement Learning Playground Inspired by ARC Raiders
- GitHub Repository: https://github.com/CarloRomeo427/ARC_RL
Robot Morphologies
The benchmark features four unique robotic body plans:
- 👑 Queen: 18-DoF hexapod.
- 🛡️ Bastion: 12-DoF armoured hexapod.
- 🐸 Leaper: 12-DoF quadruped.
- 🪲 Tick: 18-DoF compact hexapod.
The datasets provided here are hand-crafted Central Pattern Generator (CPG) demonstrations for each morphology, which serve as fixed expert references and as sources of prior data for offline-to-online reinforcement learning algorithms like SACfD, SPEQ-O2O, and SOPE.
Usage
To launch training with prior data (which automatically downloads the necessary files from this repository), use an algorithm like sacfd or sope:
python main.py --algo sacfd --env queen --log-wandb
To regenerate or collect expert episodes manually:
python -m src.utils.collect_dataset --env bastion --n-episodes 1000
Citation
@misc{romeo2026arcrlreinforcementlearningplayground,
title={ARC-RL: A Reinforcement Learning Playground Inspired by ARC Raiders},
author={Carlo Romeo and Andrew D. Bagdanov},
year={2026},
eprint={2605.19503},
archivePrefix={arXiv},
primaryClass={cs.RO},
url={https://arxiv.org/abs/2605.19503},
}
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