{"url":"/dataset/mo-gymnasium","name":"MO-Gymnasium","full_name":null,"description_markdown":"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](https://github.com/Farama-Foundation/Gymnasium) API, but return vectorized rewards as numpy arrays.","description_withheld":null,"homepage":"https://github.com/Farama-Foundation/MO-Gymnasium","introduced_date":"2022-11-30","introduced_date_note":null,"introduced_by":{"paper":"/paper/mo-gym-a-library-of-multi-objective","title":"MO-Gym: A Library of Multi-Objective Reinforcement Learning Environments","first_author":"Lucas N. Alegre","url":null},"license":{"name":"MIT","url":"https://github.com/Farama-Foundation/MO-Gymnasium/blob/main/LICENSE"},"modalities":[{"name":"Environment","url":"/datasets/modality/environment"}],"tasks":[{"name":"Continuous Control","url":"/task/continuous-control","datasets_with_task":"/datasets/task/continuous-control"},{"name":"MuJoCo Games","url":"/task/mujoco-games","datasets_with_task":"/datasets/task/mujoco-games"},{"name":"OpenAI Gym","url":"/task/openai-gym","datasets_with_task":"/datasets/task/openai-gym"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["MO-Gymnasium"],"data_loaders":[],"num_papers_in_archive":8,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}