Datasets › MO-Gymnasium

MO-Gymnasium

Introduced by Lucas N. Alegre et al. in MO-Gym: A Library of Multi-Objective Reinforcement Learning Environments30 Nov 2022 archive 2025-07-28

MO-Gymnasium is an open source Python library for developing and comparing multi-objective reinforcement learning algorithms by providing a standard API to communicate between learning algorithms and environments, as well as a standard set of environments compliant with that API. Essentially, the environments follow the standard Gymnasium API, but return vectorized rewards as numpy arrays.

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 8 papers for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

MIT

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • MO-Gymnasium

1 variant name, as the archive lists them.

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